1 Abstract

The muHVT package is a collection of R functions to facilitate building topology preserving maps for rich multivariate data analysis. Tending towards a big data preponderance, a large number of rows. A collection of R functions for this typical workflow is organized below:

Data Compression: Vector quantization (VQ), HVQ (hierarchical vector quantization) using means or medians. This step compresses the rows (long data frame) using a compression objective.
Data Projection: Dimension projection of the compressed cells to 1D,2D or 3D with the Sammons Non-linear Algorithm. This step creates topology preserving map (also called as embedding) coordinates into the desired output dimension.
Tessellation: Create cells required for object visualization using the Voronoi Tessellation method, package includes heatmap plots for hierarchical Voronoi tessellations (HVT). This step enables data insights, visualization, and interaction with the topology preserving map. Useful for semi-supervised tasks.
Prediction: Scoring new data sets and recording their assignment using the map objects from the above steps, in a sequence of maps if required.

X	price	speed	hd	ram	screen	cd	multi	premium	ads	trend
1	1499	25	80	4	14	no	no	yes	94	1
2	1795	33	85	2	14	no	no	yes	94	1
3	1595	25	170	4	15	no	no	yes	94	1
4	1849	25	170	8	14	no	no	no	94	1
5	3295	33	340	16	14	no	no	yes	94	1
6	3695	66	340	16	14	no	no	yes	94	1

Row.No	price	speed	hd	ram	screen	ads
2463	2799	50	230	8	15	216
2511	2197	33	270	4	14	216
2227	2744	50	340	8	17	275
526	2999	66	245	16	15	139
4291	1974	33	200	4	14	248
2986	2490	33	528	16	14	267

3 Map A : Base Compressed Map

Let us try to visualize the compressed Map A from the flow diagram below.

Figure 1: Flow map with highlighted bounding box in red around compressed map A

This package can perform vector quantization using the following algorithms -

Hierarchical Vector Quantization using k−means
Hierarchical Vector Quantization using k−medoids

For more information on vector quantization, refer the following link.

The HVT function constructs highly compressed hierarchical Voronoi tessellations. The raw data is first scaled and this scaled data is supplied as input to the vector quantization algorithm. The vector quantization algorithm compresses the dataset until a user-defined compression percentage/rate is achieved using a parameter called quantization error which acts as a threshold and determines the compression percentage. It means that for a given user-defined compression percentage we get the ‘n’ number of cells, then all of these cells formed will have a quantization error less than the threshold quantization error.

Let’s try to comprehend the HVT function first before moving ahead.

HVT(
  dataset,
  min_compression_perc,
  n_cells,
  depth,
  quant.err,
  distance_metric = c("L1_Norm", "L2_Norm"),
  error_metric = c("mean", "max"),
  quant_method = c("kmeans", "kmedoids"),
  normalize = TRUE,
  diagnose = FALSE,
  hvt_validation = FALSE,
  train_validation_split_ratio = 0.8
)

Each of the parameters have been explained below :

dataset - A dataframe with numeric columns. This is the input dataset on which the compression algorithm will be applied.
min_compression_perc - An integer indicating the minimum percent compression rate to be achieved for the dataset. The algorithm aims to compress the dataset while maintaining at least this specified compression percentage.
n_cells - An integer indicating the number of cells per hierarchy (level). This parameter determines the granularity or level of detail in the hierarchical vector quantization.
depth - An integer indicating the number of levels in the hierarchy. A depth of 1 means no hierarchy (single level), while higher values indicate multiple levels of hierarchy.
quant.error - A number indicating the quantization error threshold. A cell will only breakdown. into further cells if the quantization error of the cell is above the defined quantization error threshold.
projection.scale - A number indicating the scale factor for the tesselations so as to visualize the sub-tesselations. It helps in adjusting the visual representation of the hierarchy to make the sub-tesselations more visible.
scale_summary - A list with mean and standard deviation values for all the features in the dataset. Pass the scale summary when the input dataset is already scaled or normalize is set to False.
distance_metric - The distance metric can be L1_Norm or L2_Norm. L1_Norm is selected by default. The distance metric is used to calculate the distance between an n dimensional point and centroid. The user can also pass a custom function to calculate this distance.
error_metric - The error metric can be mean or max. max is selected by default. max will return the max of m values and mean will take mean of m values where each value is a distance between a point and centroid of the cell. Moreover, the user can also pass a custom function to calculate the error metric.
quant_method - The quantization method can be kmeans or kmedoids. kmeans is selected by default.
normalize - A logical value indicating whether the columns in your dataset need to be normalized. Default value is TRUE. The algorithm supports Z-score normalization.
diagnose - A logical value indicating whether user wants to perform diagnostics on the model. Default value is TRUE.
hvt_validation - A logical value indicating whether user wants to holdout a validation set and find mean absolute deviation of the validation points from the centroid. Default value is FALSE.
train_validation_split_ratio - A numeric value indicating train validation split ratio. This argument is only used when hvt_validation has been set to TRUE. Default value for the argument is 0.8.

We will use the HVT function to compress our data while preserving essential features of the dataset. Our goal is to achieve data compression upto atleast 80%. In situations where the compression ratio does not meet the desired target, we can explore adjusting the model parameters as a potential solution. This involves making modifications to parameters such as the quantization error threshold or increasing the number of cells and then rerunning the HVT function again.

In our example we will iteratively increase the number of cells until the desired compression percentage is reached instead of increasing the quantization threshold because it may reduce the level of detail captured in the data representation

First, we will construct map A by using the below mentioned model parameters.

3.0.1 Iteration 1:

We will pass the below mentioned model parameters along with training dataset (containing 5007 data poits) to HVT function.

Model Parameters

Number of Cells at each Level = 200
Maximum Depth = 1
Quantization Error Threshold = 0.2
Error Metric = Max
Distance Metric = Manhattan

set.seed(240)
map_A <- list()
map_A  <- muHVT::HVT(
  trainComputers,
  n_cells = 200,
  depth = 1,
  quant.err = 0.2,
  projection.scale = 10,
  normalize = T,
  distance_metric = "L1_Norm",
  error_metric = "max",
  quant_method = "kmeans"
)

Let’s checkout the compression summary with n_cells set to 200.

compressionSummaryTable(map_A[[3]]$compression_summary)

segmentLevel	noOfCells	noOfCellsBelowQuantizationError	percentOfCellsBelowQuantizationErrorThreshold	parameters
1	200	83	0.42	n_cells: 200 quant.err: 0.2 distance_metric: L1_Norm error_metric: max quant_method: kmeans

As it can be seen from the table above, 42% of cells have reached the quantization threshold error. Therefore we can further subdivide the cells by increasing the n_cells parameters and then see if desired compression (80%) is reached

3.0.2 Iteration 2:

Since, we are yet to achive atleast 80% compression. Let’s try to compress again using the below mentioned set of model parameters and the Computers training dataset (containing 5007 data points) .

Model Parameters

Number of Cells at each Level = 440
Maximum Depth = 1
Quantization Error Threshold = 0.2
Error Metric = Max
Distance Metric = Manhattan

map_A <- list()
map_A <-muHVT::HVT(trainComputers,
                n_cells = 440,
                quant.err = 0.2,
                depth = 1,
                distance_metric = "L1_Norm",
                error_metric = "max",
                quant_method = "kmeans",
                normalize = T)

As per the manual, map_A[[3]] gives us detailed information about the hierarchical vector quantized data. map_A[[3]][['summary']] gives a nice tabular data containing no of points, Quantization Error and the codebook.

The datatable displayed below is the summary from map A showing Cell.ID, Centroids and Quantization Error for each of the 440 cells.

summaryTable(map_A[[3]]$summary,scroll = T,limit = 500)

Segment.Level	Segment.Parent	Segment.Child	n	Cell.ID	Quant.Error	price	speed	hd	ram	screen	ads
1	1	1	7	46	0.08	-0.76	-0.89	-0.88	-0.76	-0.67	1.57
1	1	2	10	108	0.08	-0.80	-0.89	-0.16	-0.76	-0.67	0.67
1	1	3	15	223	0.12	0.37	-0.89	-0.72	-0.05	0.43	-1.65
1	1	4	11	54	0.07	-1.50	-0.89	-0.75	-0.76	-0.67	0.62
1	1	5	8	146	0.13	-0.31	0.68	-0.95	-0.89	-0.67	-0.14
1	1	6	11	150	0.16	-0.66	0.68	-0.78	-0.79	-0.67	-0.73
1	1	7	11	170	0.1	0.03	-1.24	-0.13	-0.05	-0.67	0.38
1	1	8	8	334	0.15	0.62	2.30	0.08	-0.05	0.43	0.04
1	1	9	8	114	0.07	-0.16	0.68	-1.19	-1.11	-0.67	0.87
1	1	10	7	248	0.17	0.51	-0.08	0.34	-0.05	-0.67	-0.30
1	1	11	9	140	0.12	-0.01	0.68	-1.15	-1.00	-0.67	0.33
1	1	12	7	219	0.14	-1.36	0.24	0.46	-0.05	-0.67	-0.74
1	1	13	9	271	0.05	-1.08	0.68	0.49	-0.05	0.43	-0.84
1	1	14	19	109	0.06	-0.31	-0.89	-0.74	-0.76	-0.67	0.38
1	1	15	6	176	0.08	-0.72	-0.89	-0.07	-0.05	0.43	0.72
1	1	16	17	332	0.14	0.42	2.30	0.10	-0.05	0.43	1.50
1	1	17	12	18	0.05	-1.21	-1.27	-1.19	-1.11	-0.67	0.97
1	1	18	19	149	0.16	-0.68	-0.08	-0.46	-0.76	0.43	0.79
1	1	19	17	428	0.35	0.18	2.30	2.53	1.37	0.43	-2.22
1	1	20	20	320	0.36	0.82	-0.16	-0.09	-0.12	2.64	0.71
1	1	21	3	305	0.18	2.27	-0.35	-0.01	-0.05	-0.67	-1.32
1	1	22	7	227	0.1	-0.51	-0.89	0.45	-0.05	0.43	-0.47
1	1	23	10	178	0.12	0.00	0.68	-0.86	-0.76	-0.67	-0.90
1	1	24	9	365	0.1	0.68	-0.08	1.20	1.37	0.43	-0.36
1	1	25	5	14	0.11	-1.99	-0.89	-0.96	-1.11	-0.67	0.18
1	1	26	3	411	0.05	1.25	-0.89	2.29	2.79	0.43	0.57
1	1	27	18	122	0.15	-0.18	-0.98	-0.85	-0.76	0.43	0.68
1	1	28	15	189	0.11	0.40	-0.92	0.03	-0.05	-0.67	0.87
1	1	29	11	107	0.11	-0.49	-0.96	-0.88	-0.76	-0.67	-0.64
1	1	30	7	423	0.47	3.55	0.12	2.51	1.37	-0.67	0.44
1	1	31	14	90	0.05	-0.63	-0.89	-0.79	-0.76	-0.67	0.58
1	1	32	22	430	0.24	0.63	0.75	3.07	2.79	0.43	-2.27
1	1	33	5	390	0.3	1.37	-0.89	3.73	-0.19	-0.45	0.70
1	1	34	25	101	0.18	-0.85	-0.97	-0.71	-0.76	0.43	0.84
1	1	35	11	425	0.07	0.15	2.30	1.70	1.37	0.43	-2.39
1	1	36	10	358	0.05	0.24	-0.89	1.20	1.37	0.43	-0.84
1	1	37	16	166	0.11	0.03	0.68	-1.08	-0.78	-0.67	-1.65
1	1	38	13	45	0.05	-0.91	-0.89	-1.19	-1.11	-0.67	0.42
1	1	39	8	383	0.12	1.15	2.30	0.45	1.37	-0.67	-0.16
1	1	40	5	9	0.07	-1.24	-0.97	-1.19	-1.11	-0.67	1.57
1	1	41	11	419	0.06	1.41	-0.89	2.29	2.79	0.43	-0.82
1	1	42	8	242	0.14	-0.81	-0.08	0.30	-0.05	0.43	-0.65
1	1	43	13	179	0.09	0.41	0.68	-0.76	-0.76	-0.67	0.40
1	1	44	5	375	0.04	0.06	-0.08	1.70	1.37	0.43	-0.79
1	1	45	20	129	0.14	-1.15	0.68	-0.79	-0.76	-0.67	-0.40
1	1	46	10	292	0.22	0.86	0.68	-0.65	-0.12	0.43	-1.41
1	1	47	5	79	0.12	-0.89	-1.04	-0.94	-0.05	-0.67	1.02
1	1	48	23	246	0.11	-0.42	0.68	0.46	-0.05	-0.67	-0.63
1	1	49	8	207	0.25	0.74	-0.89	-0.40	-0.40	0.43	0.52
1	1	50	11	27	0.06	-1.06	-1.27	-1.19	-1.11	-0.67	0.43
1	1	51	8	51	0.11	-1.23	-0.08	-1.05	-0.85	-0.67	0.94
1	1	52	19	288	0.09	0.81	-0.89	0.45	1.37	-0.67	0.88
1	1	53	7	154	0.1	-0.62	0.68	-0.15	-0.76	-0.67	0.84
1	1	54	10	261	0.15	0.61	-0.08	-0.67	-0.05	0.43	-1.40
1	1	55	10	195	0.15	0.18	0.77	-0.09	-0.76	-0.67	0.83
1	1	56	14	250	0.09	0.52	0.68	-0.69	-0.05	-0.67	-1.61
1	1	57	20	331	0.2	-0.63	0.68	0.30	-0.76	2.64	-0.95
1	1	58	9	379	0.15	1.33	-0.08	-0.65	-0.29	2.64	-1.52
1	1	59	14	11	0.21	-0.28	-1.05	-0.79	-0.76	2.64	0.53
1	1	60	29	359	0.13	1.36	0.68	0.18	1.37	0.43	0.77
1	1	61	6	337	0.1	2.46	0.68	0.21	-0.05	-0.67	-0.87
1	1	62	6	1	0.17	-0.17	-1.21	-1.02	-0.76	2.64	1.32
1	1	63	28	243	0.33	-0.33	2.30	-0.23	-0.46	-0.67	-0.88
1	1	64	8	274	0.07	0.41	-1.27	0.45	1.37	-0.67	0.68
1	1	65	13	362	0.14	1.07	0.75	0.35	1.37	0.43	1.34
1	1	66	10	143	0.07	-0.34	-0.89	-0.80	-0.05	-0.67	-1.66
1	1	67	4	265	0.05	-0.55	0.68	1.23	-0.05	-0.67	-0.69
1	1	68	11	13	0.15	-0.83	-0.89	-0.25	-0.76	2.64	-0.33
1	1	69	8	298	0.17	-0.62	0.20	2.29	-0.05	-0.67	-0.95
1	1	70	4	335	0.06	1.34	-0.08	0.45	1.37	-0.67	-0.08
1	1	71	20	204	0.16	0.09	-0.08	0.02	-0.05	-0.67	0.86
1	1	72	10	42	0.06	-1.49	-0.89	-0.75	-0.76	-0.67	1.04
1	1	73	1	429	0	3.08	0.68	0.04	4.20	0.43	0.71
1	1	74	14	186	0.14	-0.79	-0.89	0.45	-0.05	-0.67	-0.68
1	1	75	4	410	0.37	2.27	0.68	3.73	-0.23	-0.40	0.68
1	1	76	9	163	0.16	1.05	-0.89	-0.41	-0.60	-0.67	0.61
1	1	77	10	400	0.07	-0.03	0.68	1.70	1.37	0.43	-2.38
1	1	78	6	275	0.18	1.14	0.68	0.13	-0.05	-0.67	-0.18
1	1	79	25	241	0.16	-0.88	0.68	0.40	-0.05	-0.67	-1.06
1	1	80	6	245	0.14	-1.22	0.68	-0.30	-0.05	0.43	-0.91
1	1	81	21	120	0.16	-0.46	-0.08	-0.82	-0.62	-0.67	0.70
1	1	82	11	40	0.18	-0.93	-0.99	-1.19	-1.11	0.43	0.37
1	1	83	9	342	0.28	1.16	0.43	-0.52	-0.68	2.64	1.12
1	1	84	8	286	0.05	-0.72	1.11	0.50	-0.05	0.43	-0.83
1	1	85	8	33	0.1	-1.06	-0.89	-1.18	-1.02	-0.67	-0.99
1	1	86	5	282	0.23	-1.50	0.53	0.19	-0.48	0.43	-2.16
1	1	87	17	137	0.07	-0.31	0.68	-0.78	-0.76	-0.67	0.96
1	1	88	19	168	0.07	-0.08	-0.89	0.05	-0.05	-0.67	1.04
1	1	89	7	291	0.05	1.10	-0.89	0.15	1.37	-0.67	0.36
1	1	90	6	24	0.19	-0.97	-1.02	-1.07	-0.94	0.43	-1.40
1	1	91	4	434	0.59	4.07	1.49	1.29	0.30	2.64	0.07
1	1	92	19	409	0.65	0.92	0.42	1.41	1.37	2.64	-0.60
1	1	93	9	393	0.46	2.04	2.30	0.91	-0.05	-0.31	-0.34
1	1	94	8	22	0.08	-1.66	-1.27	-0.84	-0.76	-0.67	0.84
1	1	95	23	158	0.22	-1.41	0.68	-0.20	-0.70	-0.67	-1.05
1	1	96	11	330	0.22	1.55	0.68	-0.45	-0.31	0.43	-1.59
1	1	97	6	145	0.17	0.49	-0.89	-0.64	-0.76	-0.67	-0.17
1	1	98	12	121	0.15	0.21	-0.89	-0.80	-0.76	-0.67	-1.70
1	1	99	14	329	0.24	2.06	0.63	0.31	-0.25	0.43	0.99
1	1	100	16	299	0.05	1.21	-0.89	0.46	1.37	-0.67	0.86
1	1	101	5	328	0.1	-0.87	1.11	1.33	-0.05	0.43	-1.13
1	1	102	10	278	0.1	0.33	-0.93	0.45	1.37	-0.67	0.02
1	1	103	5	102	0.1	-1.05	0.68	-0.76	-0.76	-0.67	1.27
1	1	104	12	25	0.08	-1.25	-1.05	-0.78	-0.76	-0.67	1.57
1	1	105	9	385	0.25	2.05	0.34	-0.21	-0.05	2.64	1.12
1	1	106	10	231	0.18	-0.02	-0.08	0.02	-0.05	0.43	1.29
1	1	107	5	193	0.14	-0.66	-0.08	-0.33	-0.05	-0.67	-1.01
1	1	108	4	418	0.06	-0.03	0.68	3.07	1.37	0.43	-2.25
1	1	109	4	306	0.16	1.83	0.68	-0.59	-0.05	-0.67	-1.57
1	1	110	5	378	0.15	1.09	0.68	1.20	1.37	0.43	-0.11
1	1	111	2	308	0.07	-0.55	0.68	0.26	1.37	-0.67	-1.25
1	1	112	18	239	0.15	0.44	0.75	0.08	-0.05	-0.67	1.05
1	1	113	11	62	0.06	-1.14	-0.89	-0.81	-0.76	-0.67	0.73
1	1	114	5	169	0.07	-0.26	-0.89	0.47	-0.05	-0.67	1.40
1	1	115	18	415	0.11	0.74	-0.08	2.29	2.79	0.43	-0.93
1	1	116	5	97	0.13	0.23	-1.19	-1.05	-0.76	-0.67	0.77
1	1	117	24	19	0.22	-0.06	2.30	-0.89	-0.89	-0.67	1.18
1	1	118	9	184	0.17	-0.98	0.34	-0.29	-0.05	-0.67	-0.08
1	1	119	11	43	0.12	-0.82	-0.89	-1.04	-0.79	-0.67	-1.65
1	1	120	9	257	0.29	2.17	-0.62	0.10	-0.05	-0.55	0.65
1	1	121	27	155	0.18	0.15	0.68	-0.84	-0.76	-0.67	0.81
1	1	122	20	215	0.11	0.33	-0.08	-0.69	-0.05	-0.67	-1.64
1	1	123	14	348	0.24	0.61	0.74	0.37	1.37	0.43	0.25
1	1	124	13	162	0.12	0.01	-1.01	-0.67	-0.05	-0.67	-1.57
1	1	125	7	366	0.22	1.62	0.35	-0.29	1.37	-0.67	-1.65
1	1	126	9	77	0.02	-0.88	-0.89	-0.78	-0.76	-0.67	0.66
1	1	127	25	253	0.14	0.70	0.68	0.16	-0.05	-0.67	0.61
1	1	128	9	84	0.09	-0.27	-1.27	-0.81	-0.76	-0.67	0.81
1	1	129	3	398	0.04	-0.03	-0.08	2.29	1.37	0.43	-1.98
1	1	130	9	412	0.05	0.90	-0.89	2.29	2.79	0.43	-0.48
1	1	131	8	309	0.06	1.43	-0.89	0.41	1.37	-0.67	0.46
1	1	132	8	267	0.08	0.10	0.68	0.37	-0.05	0.43	1.57
1	1	133	16	252	0.22	0.94	-0.08	-0.40	-0.14	0.43	0.43
1	1	134	15	119	0.13	-0.60	-0.99	-0.75	-0.76	0.43	0.24
1	1	135	13	48	0.09	-0.66	-0.92	-1.19	-1.11	-0.67	0.82
1	1	136	9	326	0.11	1.45	-0.08	0.32	1.37	-0.67	0.38
1	1	137	11	386	0.22	1.37	0.68	-0.66	-0.18	2.64	-1.36
1	1	138	20	255	0.15	0.43	-0.89	-0.34	-0.05	2.64	0.68
1	1	139	8	161	0.14	-0.68	-0.94	-0.08	-0.05	0.43	1.41
1	1	140	10	38	0.13	-1.22	-1.19	-0.92	-0.76	0.43	0.91
1	1	141	14	180	0.12	0.09	0.68	-0.56	-0.76	-0.67	0.07
1	1	142	13	427	0.21	2.01	0.62	2.29	2.79	0.43	-0.18
1	1	143	15	354	0.13	1.63	0.68	0.39	1.37	-0.67	0.26
1	1	144	11	301	0.14	0.82	-1.03	0.15	1.37	-0.67	-0.85
1	1	145	7	205	0.13	0.24	-0.08	-0.05	-0.05	-0.67	1.57
1	1	146	10	327	0.14	0.66	0.68	0.60	1.37	-0.67	0.42
1	1	147	11	403	0.11	0.92	2.30	1.22	1.37	0.43	-0.79
1	1	148	7	127	0.08	-0.20	-0.89	-0.10	-0.76	-0.67	0.69
1	1	149	6	217	0.11	0.41	-0.89	0.26	-0.05	-0.67	-0.34
1	1	150	11	323	0.1	0.96	-0.89	0.46	1.37	0.43	0.72
1	1	151	9	208	0.16	0.16	0.68	-0.60	-0.05	-0.67	0.43
1	1	152	14	405	0.14	-0.04	0.68	2.29	1.37	0.43	-2.24
1	1	153	10	98	0.08	-0.22	-0.89	-1.14	-0.76	-0.67	0.33
1	1	154	7	47	0.05	-0.99	-0.89	-1.16	-0.76	-0.67	1.03
1	1	155	8	182	0.15	-1.00	0.68	0.08	-0.76	-0.67	-0.46
1	1	156	9	153	0.07	-0.24	-0.93	0.04	-0.05	-0.67	1.57
1	1	157	23	65	0.08	-1.23	-0.89	-0.82	-0.76	-0.67	0.27
1	1	158	4	367	0.08	3.03	-0.08	0.15	-0.05	-0.67	-1.65
1	1	159	29	421	0.15	1.04	0.68	2.29	2.79	0.43	-0.84
1	1	160	10	111	0.14	-1.33	-0.89	0.06	-0.76	-0.67	-0.65
1	1	161	13	382	0.25	3.03	0.68	0.23	-0.05	-0.42	-1.68
1	1	162	10	142	0.1	-0.54	-0.89	-0.76	-0.05	-0.67	-0.73
1	1	163	14	433	0.32	1.31	-0.10	2.29	2.79	2.64	-0.81
1	1	164	14	50	0.08	-0.88	-0.08	-1.19	-1.11	-0.67	0.91
1	1	165	23	125	0.14	-0.78	0.68	-0.84	-0.76	-0.67	0.41
1	1	166	7	67	0.09	-0.95	0.68	-1.13	-0.96	-0.67	1.03
1	1	167	12	254	0.11	-0.53	0.68	0.02	-0.05	0.43	-0.24
1	1	168	11	113	0.17	-0.63	-0.08	-0.98	-0.92	-0.67	-0.30
1	1	169	9	83	0.04	-0.71	-0.89	-0.75	-0.76	-0.67	0.76
1	1	170	10	89	0.11	-1.18	-0.93	-0.19	-0.76	-0.67	0.66
1	1	171	8	44	0.06	-1.41	-0.89	-1.13	-0.76	-0.67	0.36
1	1	172	8	310	0.08	1.13	-0.99	0.45	1.37	-0.67	-0.08
1	1	173	8	6	0.08	-1.21	-0.89	-1.28	-1.11	-0.67	-1.64
1	1	174	14	295	0.12	-0.78	-0.08	0.38	-0.76	2.64	-1.00
1	1	175	12	316	0.19	1.00	-1.02	-0.29	1.37	-0.67	-1.61
1	1	176	2	346	0.15	0.38	-0.11	2.60	-0.05	0.43	0.69
1	1	177	12	194	0.17	-0.92	0.68	-0.46	-0.76	0.43	-0.16
1	1	178	17	396	0.19	1.51	2.30	0.45	1.37	-0.09	1.34
1	1	179	15	206	0.13	-1.30	-0.08	0.26	-0.76	0.43	-0.90
1	1	180	4	322	0.13	1.35	-0.89	-0.06	1.37	0.43	0.52
1	1	181	31	225	0.12	-0.25	0.68	0.14	-0.05	-0.67	0.21
1	1	182	5	185	0.14	0.46	-0.57	-0.29	-0.76	0.43	1.27
1	1	183	12	103	0.15	-0.68	-0.08	-0.63	-0.76	-0.67	1.39
1	1	184	2	151	0.06	-0.29	-0.89	0.06	-0.76	-0.67	-0.87
1	1	185	11	232	0.12	-0.39	0.68	0.22	-0.05	-0.67	-0.20
1	1	186	9	313	0.29	0.41	-0.89	1.32	1.37	-0.67	0.31
1	1	187	17	372	0.15	0.23	0.70	1.21	1.37	0.43	-0.74
1	1	188	9	407	0.09	0.41	2.30	1.70	1.37	0.43	-1.08
1	1	189	14	68	0.36	-0.83	0.19	-1.16	-1.09	0.43	0.95
1	1	190	9	37	0.08	-1.53	-1.27	-0.83	-0.76	-0.67	0.41
1	1	191	8	28	0.13	-1.33	-1.22	-1.10	-0.85	-0.67	-0.62
1	1	192	8	71	0.24	-1.65	-0.89	-0.19	-0.67	-0.67	0.43
1	1	193	9	7	0.2	-0.89	-0.89	-0.36	-0.84	2.64	0.50
1	1	194	16	53	0.05	-1.15	-0.89	-0.82	-0.76	-0.67	1.06
1	1	195	9	29	0.07	-0.60	-1.27	-1.08	-0.76	-0.67	-1.66
1	1	196	14	377	0.21	2.10	0.68	0.25	1.37	0.43	0.77
1	1	197	10	190	0.2	-0.45	-0.73	-0.74	-0.05	0.43	-0.77
1	1	198	11	15	0.13	-1.32	-1.03	-1.19	-1.11	0.43	0.88
1	1	199	13	344	0.23	0.11	0.68	0.14	-0.05	2.64	-0.39
1	1	200	12	128	0.1	0.05	-0.08	-0.81	-0.76	-0.67	0.90
1	1	201	17	36	0.06	-1.25	-1.27	-1.13	-0.76	-0.67	0.40
1	1	202	12	172	0.1	-0.33	-0.89	-0.44	-0.05	0.43	0.94
1	1	203	8	293	0.04	-0.74	1.11	0.50	-0.05	0.43	-1.22
1	1	204	4	165	0.06	0.02	-0.89	-0.67	-0.76	0.43	-1.69
1	1	205	13	187	0.13	0.43	-0.89	-0.71	-0.05	-0.67	-1.63
1	1	206	4	210	0.13	0.00	2.30	-0.78	-0.76	0.43	0.94
1	1	207	12	70	0.05	-0.72	-1.27	-0.81	-0.76	-0.67	0.69
1	1	208	13	156	0.14	0.14	-0.08	-0.21	-0.76	-0.67	0.93
1	1	209	10	317	0.17	0.87	2.30	0.21	-0.05	-0.67	1.31
1	1	210	19	197	0.23	-0.12	0.68	-0.79	-0.83	0.43	0.37
1	1	211	13	201	0.15	0.33	-0.98	-0.29	-0.05	-0.67	-0.85
1	1	212	12	94	0.15	-1.25	-0.08	-0.80	-0.76	-0.67	0.38
1	1	213	26	85	0.09	-0.35	-0.89	-0.98	-0.76	-0.67	-1.63
1	1	214	13	324	0.11	0.51	2.30	0.21	-0.05	0.43	0.66
1	1	215	9	95	0.08	-0.54	0.68	-1.18	-1.07	-0.67	1.01
1	1	216	23	126	0.14	-0.21	-0.08	-1.01	-0.77	-0.67	-1.64
1	1	217	10	256	0.2	0.88	0.68	-0.39	-0.05	-0.67	-0.79
1	1	218	19	356	0.34	-0.96	0.52	1.97	-0.20	-0.67	-2.18
1	1	219	14	147	0.11	0.17	-0.08	-0.77	-0.76	-0.67	0.27
1	1	220	14	240	0.2	0.44	0.86	0.03	-0.10	-0.67	1.57
1	1	221	13	191	0.18	0.14	-0.08	-0.75	-0.49	0.43	0.67
1	1	222	7	380	0.05	0.04	-0.08	1.70	1.37	0.43	-1.23
1	1	223	18	88	0.05	-0.46	-0.89	-0.77	-0.76	-0.67	1.00
1	1	224	12	417	0.1	1.69	0.68	2.29	2.79	-0.67	0.38
1	1	225	18	413	0.27	2.56	0.68	-0.04	1.37	2.64	0.59
1	1	226	9	401	0.08	0.81	-0.89	1.20	1.37	2.64	-0.61
1	1	227	8	49	0.08	-1.28	-0.89	-0.29	-0.76	-0.67	1.41
1	1	228	8	12	0.18	-1.32	-1.03	-0.93	-0.85	0.43	1.57
1	1	229	6	237	0.19	0.49	0.17	-0.73	-0.76	0.43	-1.52
1	1	230	16	266	0.12	-0.03	0.68	0.49	-0.05	0.43	0.54
1	1	231	5	82	0.12	-1.25	-1.12	-0.29	-0.05	-0.67	1.27
1	1	232	24	110	0.12	-0.42	-1.00	-0.71	-0.76	-0.67	-0.07
1	1	233	14	270	0.15	0.34	-1.11	0.45	1.37	-0.67	1.39
1	1	234	4	200	0.07	-0.30	-0.89	0.26	-0.05	0.43	1.57
1	1	235	16	263	0.29	0.70	0.35	-0.52	-0.18	0.43	-0.62
1	1	236	12	280	0.21	1.35	0.68	-0.41	-0.23	0.43	0.90
1	1	237	8	281	0.07	-0.96	0.68	0.48	-0.05	0.43	-1.23
1	1	238	7	287	0.13	0.20	0.68	0.45	-0.05	0.43	-0.55
1	1	239	16	116	0.18	-1.23	-0.08	-0.57	-0.76	-0.67	-0.37
1	1	240	31	321	0.42	-0.50	2.30	0.40	-0.12	-0.03	-1.00
1	1	241	16	420	0.13	1.51	-0.08	2.29	2.79	0.43	-0.49
1	1	242	8	199	0.12	0.05	-1.03	0.20	-0.05	-0.67	-0.07
1	1	243	8	314	0.07	0.99	-0.08	0.45	1.37	-0.67	0.72
1	1	244	7	289	0.06	-0.20	0.68	1.23	-0.05	0.43	0.35
1	1	245	15	216	0.16	-0.16	0.68	0.03	-0.05	-0.67	0.76
1	1	246	14	273	0.16	0.31	0.63	0.14	-0.05	0.43	0.07
1	1	247	20	132	0.18	-0.76	-0.08	-0.14	-0.72	-0.67	0.74
1	1	248	5	369	0.08	-0.74	0.68	1.70	-0.05	0.43	-2.35
1	1	249	11	432	0.33	0.40	1.35	2.13	1.37	2.64	-2.28
1	1	250	6	341	0.22	0.46	0.62	0.21	1.37	0.43	1.36
1	1	251	24	404	0.12	1.30	-0.89	2.29	2.79	-0.67	0.33
1	1	252	9	63	0.05	-1.23	-0.89	-0.75	-0.76	-0.67	0.65
1	1	253	11	226	0.16	0.32	-0.96	-0.44	-0.05	0.43	-0.89
1	1	254	11	133	0.09	-0.43	-0.89	-0.75	-0.05	-0.67	0.33
1	1	255	19	376	0.16	0.60	0.68	1.17	1.37	0.43	-0.70
1	1	256	8	80	0.06	-0.23	-0.89	-1.15	-0.76	-0.67	0.91
1	1	257	13	164	0.27	-0.58	0.15	-0.89	-0.87	0.43	-0.58
1	1	258	7	78	0.07	-0.82	-0.89	-0.29	-0.76	-0.67	1.33
1	1	259	5	422	0.05	1.83	-0.89	2.29	2.79	0.43	-0.23
1	1	260	10	23	0.11	-1.45	-1.23	-1.16	-0.83	-0.67	-0.10
1	1	261	8	60	0.05	-0.57	-1.27	-1.14	-0.76	-0.67	0.44
1	1	262	12	93	0.12	-0.88	-0.92	-0.78	-0.76	-0.67	-0.41
1	1	263	20	279	0.24	0.33	2.30	0.14	-0.19	-0.67	0.31
1	1	264	15	75	0.05	-0.67	-0.89	-1.10	-0.76	-0.67	0.39
1	1	265	15	351	0.04	0.27	-0.89	1.20	1.37	0.43	-0.45
1	1	266	7	408	0.25	2.71	-0.89	-0.27	1.37	2.64	0.06
1	1	267	10	57	0.07	-0.55	-1.27	-1.15	-0.76	-0.67	0.82
1	1	268	13	387	0.24	0.11	0.68	1.48	-0.05	2.64	-0.61
1	1	269	6	436	0.27	1.23	2.30	1.91	2.08	2.64	-1.04
1	1	270	11	202	0.09	0.20	-0.89	0.47	-0.05	-0.67	0.68
1	1	271	12	402	0.47	1.54	0.81	2.42	1.37	0.34	0.54
1	1	272	12	152	0.15	-0.05	-0.08	-0.83	-0.76	-0.67	-0.87
1	1	273	9	21	0.09	-1.48	-0.89	-1.15	-0.96	-0.67	0.95
1	1	274	11	69	0.05	-0.74	-0.89	-0.84	-0.76	-0.67	1.11
1	1	275	14	249	0.24	-0.06	-0.77	-0.01	-0.15	2.64	0.62
1	1	276	4	318	0.08	-1.02	0.68	1.35	-0.05	0.43	-1.21
1	1	277	19	247	0.15	0.09	0.68	-0.36	-0.05	0.43	0.65
1	1	278	14	297	0.17	1.23	0.68	0.23	-0.05	0.43	0.58
1	1	279	8	338	0.08	0.88	0.68	0.45	1.37	-0.67	1.41
1	1	280	13	171	0.1	-0.38	-0.92	0.00	-0.05	-0.67	0.06
1	1	281	14	371	0.28	-0.93	2.30	0.46	-0.20	-0.12	-2.31
1	1	282	24	173	0.33	-0.28	0.73	-0.75	-0.82	0.43	0.97
1	1	283	18	355	0.14	1.38	0.68	-0.21	1.37	0.43	0.42
1	1	284	4	345	0.11	0.83	-0.49	-0.66	1.37	0.43	-1.59
1	1	285	11	56	0.05	-0.83	-1.27	-0.78	-0.76	-0.67	1.01
1	1	286	7	370	0.19	1.55	0.68	-0.38	1.37	0.43	-1.02
1	1	287	10	64	0.06	-0.48	-0.89	-1.19	-1.11	-0.67	0.41
1	1	288	9	167	0.15	-0.36	-0.89	-0.71	-0.05	0.43	0.29
1	1	289	6	124	0.15	-1.28	-1.02	-0.29	-0.05	-0.67	-0.30
1	1	290	14	272	0.11	-0.70	0.68	0.43	-0.05	0.43	-0.78
1	1	291	25	188	0.09	0.21	-0.89	0.05	-0.05	-0.67	0.52
1	1	292	23	435	0.3	1.05	2.30	2.59	2.79	0.43	-1.56
1	1	293	8	8	0.08	-1.66	-1.27	-1.18	-0.94	-0.67	1.07
1	1	294	14	431	0.2	2.14	2.30	2.29	2.79	-0.60	0.40
1	1	295	3	96	0.08	-0.16	-0.89	-0.58	-0.76	-0.67	1.57
1	1	296	9	87	0.06	-0.46	-1.27	-0.78	-0.76	-0.67	0.39
1	1	297	6	414	0.04	0.90	-0.89	2.29	2.79	0.43	-0.85
1	1	298	10	230	0.18	0.31	-0.89	0.32	-0.12	0.43	0.71
1	1	299	13	58	0.11	-0.84	-0.95	-1.16	-0.98	-0.67	-0.08
1	1	300	11	4	0.31	0.63	-1.03	-0.85	-0.76	2.64	0.96
1	1	301	24	277	0.18	0.59	0.68	0.21	-0.08	0.43	0.76
1	1	302	13	130	0.1	-0.85	-0.08	-0.61	-0.76	-0.67	-0.80
1	1	303	6	131	0.17	-0.53	0.68	-0.61	-0.52	-0.67	1.57
1	1	304	10	55	0.09	-1.09	-1.27	-0.81	-0.76	-0.67	0.53
1	1	305	21	269	0.11	-1.16	0.68	0.48	-0.05	-0.67	-2.25
1	1	306	21	91	0.1	-0.45	-0.08	-1.19	-1.11	-0.67	0.57
1	1	307	9	104	0.08	-0.46	-0.98	-0.87	-0.76	-0.67	-1.12
1	1	308	19	32	0.07	-1.02	-0.89	-1.19	-1.11	-0.67	0.97
1	1	309	4	268	0.13	0.22	-0.89	0.07	-0.05	2.64	1.46
1	1	310	4	59	0.03	-0.93	-0.89	-1.14	-0.76	-0.67	0.69
1	1	311	4	2	0.12	-0.52	-0.89	-0.66	-0.76	2.64	1.22
1	1	312	8	3	0.15	-1.66	-1.22	-1.08	-0.89	-0.67	1.57
1	1	313	8	141	0.14	-0.61	-0.89	-0.21	-0.76	0.43	0.62
1	1	314	14	183	0.08	-0.35	-0.89	0.45	-0.05	-0.67	0.46
1	1	315	6	192	0.15	0.62	-0.89	-0.58	-0.76	0.43	-0.26
1	1	316	6	196	0.17	-0.81	-0.76	-0.07	-0.05	0.43	0.02
1	1	317	15	92	0.04	-0.75	-0.89	-0.75	-0.76	-0.67	0.36
1	1	318	6	214	0.21	1.06	0.17	-0.90	-0.64	-0.67	-1.66
1	1	319	9	389	0.05	0.14	0.68	1.70	1.37	0.43	-1.23
1	1	320	8	381	0.26	-0.31	2.30	1.86	-0.05	-0.12	-0.99
1	1	321	2	438	0.38	2.15	1.49	6.57	1.37	0.43	-0.28
1	1	322	18	224	0.09	-0.62	0.68	0.03	-0.05	-0.67	-0.65
1	1	323	7	361	0.05	0.63	-0.89	1.20	1.37	0.43	-0.72
1	1	324	8	352	0.12	0.50	-0.89	1.20	1.37	0.43	-0.08
1	1	325	8	234	0.1	-0.43	0.68	-0.12	-0.05	0.43	1.46
1	1	326	4	17	0.04	-1.04	-0.08	-1.19	-1.11	-0.67	1.57
1	1	327	3	5	0.04	-2.07	-0.89	-1.18	-1.11	-0.67	0.90
1	1	328	9	304	0.1	-0.22	0.68	1.23	-0.05	0.43	-0.46
1	1	329	9	350	0.09	-1.17	2.30	0.45	-0.76	-0.67	-2.26
1	1	330	12	294	0.1	0.98	-0.92	0.45	1.37	-0.67	0.42
1	1	331	9	307	0.16	0.42	-1.14	0.45	1.37	0.43	1.02
1	1	332	9	439	0.49	1.48	1.28	4.62	3.89	0.92	-2.46
1	1	333	10	148	0.16	-1.03	-0.57	-0.22	-0.76	0.43	-0.12
1	1	334	6	424	0.25	1.52	2.30	0.32	1.37	2.64	0.77
1	1	335	19	52	0.13	-1.61	-0.91	-0.75	-0.78	-0.67	-0.31
1	1	336	12	31	0.05	-1.28	-0.89	-1.19	-1.11	-0.67	0.60
1	1	337	19	123	0.2	-1.52	-0.08	-0.20	-0.76	-0.67	-0.94
1	1	338	11	218	0.17	-1.37	0.54	0.45	-0.76	-0.67	-2.18
1	1	339	18	262	0.2	0.88	0.68	-0.51	-0.17	0.43	0.51
1	1	340	3	325	0.07	-1.02	0.68	0.58	-0.05	0.43	-2.46
1	1	341	7	212	0.1	-1.39	0.68	-0.26	-0.76	0.43	-1.09
1	1	342	12	41	0.1	-1.75	-0.92	-0.62	-0.76	-0.67	-0.88
1	1	343	7	290	0.08	0.87	-1.27	0.46	1.37	-0.67	0.86
1	1	344	8	139	0.12	-1.50	-0.89	0.01	-0.76	0.43	-0.63
1	1	345	14	360	0.27	2.68	0.68	0.44	-0.25	0.43	0.22
1	1	346	6	181	0.05	-0.41	-0.89	-0.29	-0.05	0.43	0.55
1	1	347	13	353	0.11	1.54	0.68	0.47	1.37	-0.67	0.87
1	1	348	8	349	0.13	1.34	0.30	0.15	1.37	-0.67	-0.87
1	1	349	6	61	0.04	-0.65	-0.89	-1.14	-0.76	-0.67	0.94
1	1	350	21	336	0.25	0.45	0.68	0.04	-0.12	2.64	0.86
1	1	351	12	235	0.26	-0.42	0.36	-0.39	-0.76	2.64	0.12
1	1	352	10	115	0.16	-1.06	-1.08	-0.38	-0.05	-0.67	0.60
1	1	353	5	339	0.15	-0.28	0.22	2.29	-0.05	0.43	-0.55
1	1	354	16	397	0.34	-0.72	2.30	1.86	-0.14	-0.26	-2.30
1	1	355	4	236	0.15	-0.45	0.68	-0.08	-0.05	-0.67	-1.43
1	1	356	11	160	0.1	-0.31	-1.27	0.12	-0.05	-0.67	0.58
1	1	357	15	10	0.12	-1.28	-1.27	-1.05	-0.83	-0.67	-1.64
1	1	358	4	392	0.2	0.97	2.30	0.54	1.37	0.43	0.28
1	1	359	10	144	0.11	0.46	-0.89	-0.29	-0.76	-0.67	0.75
1	1	360	7	213	0.07	-0.32	-0.89	0.48	-0.05	0.43	0.59
1	1	361	9	394	0.28	2.75	0.68	-0.09	-0.29	2.64	0.44
1	1	362	7	340	0.2	0.97	-1.00	0.03	1.37	0.43	-0.83
1	1	363	21	251	0.24	1.15	0.68	-0.21	-0.12	-0.67	0.79
1	1	364	11	118	0.1	0.14	-0.89	-0.84	-0.76	-0.67	0.42
1	1	365	12	99	0.04	-0.35	-0.89	-0.79	-0.76	-0.67	0.76
1	1	366	8	388	0.15	1.15	2.30	0.73	1.37	-0.67	0.52
1	1	367	8	260	0.14	0.41	0.68	0.40	-0.05	-0.67	-0.36
1	1	368	12	117	0.09	-0.93	-0.89	-0.04	-0.76	-0.67	0.01
1	1	369	12	303	0.05	-0.52	0.68	1.23	-0.05	0.43	-0.83
1	1	370	7	395	0.21	1.06	2.30	0.16	-0.05	2.64	0.75
1	1	371	17	81	0.13	-1.49	-0.91	-0.30	-0.76	-0.67	-0.20
1	1	372	10	209	0.28	0.96	0.60	-0.64	-0.76	-0.67	-0.04
1	1	373	17	66	0.08	-1.33	-0.89	-0.81	-0.76	-0.67	-0.51
1	1	374	14	136	0.12	-0.28	-0.92	-0.50	-0.05	-0.67	1.05
1	1	375	20	198	0.09	-0.42	-0.89	0.45	-0.05	-0.67	-0.41
1	1	376	16	26	0.08	-1.40	-1.27	-1.15	-0.76	-0.67	0.81
1	1	377	7	343	0.22	0.87	-0.89	-0.65	-0.35	2.64	-1.45
1	1	378	10	39	0.06	-1.04	-1.27	-1.11	-0.76	-0.67	0.91
1	1	379	8	229	0.09	0.17	0.68	-0.63	-0.05	-0.67	-0.85
1	1	380	15	175	0.14	0.41	-0.89	-0.46	-0.05	-0.67	0.41
1	1	381	13	35	0.07	-1.28	-1.27	-0.82	-0.76	-0.67	1.03
1	1	382	14	220	0.09	-0.81	-0.08	0.45	-0.05	-0.67	-0.96
1	1	383	11	283	0.12	0.38	2.30	-0.05	-0.05	-0.67	1.46
1	1	384	10	134	0.12	-0.09	1.02	-0.78	-0.76	-0.67	1.36
1	1	385	14	416	0.08	1.33	-0.89	2.29	2.79	0.43	-0.30
1	1	386	15	76	0.18	-1.35	-0.94	-0.63	-0.81	0.43	0.43
1	1	387	23	157	0.08	-0.37	-0.89	-0.04	-0.05	-0.67	0.67
1	1	388	4	391	0.26	1.95	0.49	0.42	-0.05	2.64	0.27
1	1	389	6	105	0.08	-0.68	0.68	-1.25	-1.11	-0.67	-1.44
1	1	390	8	315	0.16	0.60	-1.08	0.37	1.37	0.43	0.25
1	1	391	14	72	0.04	-0.78	-0.89	-0.76	-0.76	-0.67	0.96
1	1	392	8	259	0.15	0.35	0.79	-0.12	-0.05	0.43	1.28
1	1	393	18	222	0.1	-0.38	-0.08	0.45	-0.05	-0.67	-0.53
1	1	394	11	333	0.06	1.49	-0.08	0.46	1.37	-0.67	0.89
1	1	395	15	276	0.1	-0.28	0.68	0.32	-0.05	0.43	-0.74
1	1	396	9	16	0.11	-1.53	-1.27	-1.19	-1.03	-0.67	0.53
1	1	397	9	364	0.08	0.27	-0.08	1.20	1.37	0.43	-0.75
1	1	398	10	211	0.14	0.00	-1.00	-0.05	-0.05	0.43	0.18
1	1	399	7	384	0.25	0.30	0.74	1.76	1.37	0.43	-0.80
1	1	400	6	177	0.14	1.15	-0.08	-0.61	-0.76	-0.67	0.67
1	1	401	19	203	0.11	-0.13	-1.01	0.05	-0.05	0.43	0.76
1	1	402	8	312	0.09	0.73	-0.08	0.45	1.37	-0.67	1.41
1	1	403	9	258	0.2	-0.18	-0.89	2.29	-0.05	-0.67	-0.38
1	1	404	11	244	0.16	-1.09	0.68	0.39	-0.76	0.43	-0.94
1	1	405	11	319	0.21	0.03	0.54	2.29	-0.05	-0.67	-0.36
1	1	406	15	159	0.08	-0.10	-1.27	0.08	-0.05	-0.67	0.91
1	1	407	33	221	0.14	0.64	-0.08	-0.05	-0.05	-0.67	0.68
1	1	408	11	112	0.09	-0.50	0.68	-1.18	-1.08	-0.67	0.48
1	1	409	17	399	0.31	1.42	0.73	0.26	1.37	2.64	0.75
1	1	410	5	20	0.08	-1.28	-1.27	-1.05	-0.90	-0.67	-1.12
1	1	411	6	34	0.08	-0.85	-0.08	-1.25	-1.11	-0.67	-1.44
1	1	412	6	426	0.2	3.36	0.68	-0.27	1.37	2.64	-0.22
1	1	413	12	285	0.1	0.72	-1.24	0.30	1.37	-0.67	0.32
1	1	414	8	363	0.08	1.28	1.11	0.45	1.37	-0.67	1.36
1	1	415	8	437	0.27	1.02	1.00	3.07	2.79	2.64	-2.30
1	1	416	7	284	0.19	0.20	-0.66	-0.74	-0.05	2.64	-0.71
1	1	417	9	264	0.06	0.29	-0.89	0.45	1.37	-0.67	0.66
1	1	418	21	238	0.21	0.24	-0.08	-0.09	-0.05	0.43	0.69
1	1	419	3	296	0.02	-0.47	0.68	0.03	-0.05	0.43	-2.34
1	1	420	10	100	0.16	-0.44	-0.97	-0.87	-0.76	0.43	1.21
1	1	421	11	174	0.15	-0.61	0.68	-0.02	-0.76	-0.67	0.17
1	1	422	9	311	0.25	1.52	-0.53	-0.55	-0.76	2.64	0.36
1	1	423	6	135	0.09	-0.58	-1.27	0.12	-0.05	-0.67	1.29
1	1	424	5	368	0.15	2.37	0.68	0.36	1.37	-0.67	0.68
1	1	425	9	373	0.12	1.65	0.68	0.39	1.37	0.43	-0.01
1	1	426	10	228	0.13	0.42	-0.08	-0.33	-0.05	-0.67	-0.92
1	1	427	20	86	0.22	-1.23	-0.93	-0.85	-0.83	0.43	-0.46
1	1	428	7	106	0.06	-0.07	-0.89	-0.76	-0.76	-0.67	0.98
1	1	429	8	138	0.12	-0.45	-0.99	-0.78	-0.76	0.43	-0.77
1	1	430	8	30	0.12	-0.51	1.05	-1.19	-1.11	-0.67	1.36
1	1	431	19	357	0.16	1.03	0.68	-0.27	-0.05	2.64	0.61
1	1	432	20	406	0.38	0.02	2.30	0.99	-0.05	2.64	-1.12
1	1	433	10	302	0.26	1.83	0.53	-0.09	-0.33	0.43	0.24
1	1	434	5	73	0.04	-0.72	-0.89	-0.95	-0.76	-0.67	0.82
1	1	435	1	440	0	5.51	0.68	3.07	4.20	2.64	0.50
1	1	436	14	300	0.29	2.04	0.68	0.38	-0.15	-0.67	0.69
1	1	437	19	74	0.1	-1.10	-0.89	-0.81	-0.76	-0.67	-0.90
1	1	438	7	347	0.13	1.21	-0.08	0.41	1.37	0.43	0.59
1	1	439	31	374	0.28	-0.27	0.87	0.49	-0.05	2.64	-1.24
1	1	440	17	233	0.2	-0.48	0.68	-0.10	-0.13	0.43	0.60

Now let us understand what each column in the above table means:

Segment.Level - Level of the cell. In this case, we have performed Vector Quantization for depth 1. Hence Segment Level is 1.
Segment.Parent - Parent segment of the cell.
Segment.Child (Cell.Number) - The children of a particular cell. In this case, it is the total number of cells at which we achieved the defined compression percentage.
n - No of points in each cell.
Cell.ID - Cell_ID’s are generated for the multivariate data using 1-D Sammon’s Projection algorithm.
Quant.Error - Quantization Error for each cell.

All the columns after this will contain centroids for each cell. They can also be called a codebook, which represents a collection of all centroids or codewords.

Now, let’s check the compression summary for HVT (map A) where n_cell was set to 440. The table below shows no of cells, no of cells having quantization error below threshold and percentage of cells having quantization error below threshold for each level.

mapA_compression_summary <- map_A[[3]]$compression_summary %>%  dplyr::mutate_if(is.numeric, funs(round(.,4)))
compressionSummaryTable(mapA_compression_summary)

segmentLevel	noOfCells	noOfCellsBelowQuantizationError	percentOfCellsBelowQuantizationErrorThreshold	parameters
1	440	355	0.81	n_cells: 440 quant.err: 0.2 distance_metric: L1_Norm error_metric: max quant_method: kmeans

As it can be seen from the table above, 81% of the cells have hit the quantization threshold error.Since we are successfully able to attain the desired compression percentage, so we will not further subdivide the cells

Now let’s try to understand plotHVT function. The parameters have been explained in detail below:

plotHVT(hvt.results, line.width, color.vec, pch1 = 21, centroid.size = 3, title = NULL, maxDepth = 1)

hvt.results - A list containing the output of the HVT function which has the details of the tessellations to be plotted.
line.width - A vector indicating the line widths of the tessellation boundaries for each layer.
color.vec - A vector indicating the colors of the tessellations boundaries at each layer.
pch1 - Symbol, It plots the centroids with a particular symbol such as (solid circle, bullet, filled square, filled diamond) in the tessellations (parent levels).(default = 21 i.e filled circle).
centroid.size - Size of centroids of first level tessellations (default = 3).
title - Set a title for the plot (default = NULL).

Let’s plot the Voronoi tessellation for layer 1 (map A).

muHVT::plotHVT(map_A,
        line.width = c(0.4), 
        color.vec = c("#141B41"),
        centroid.size = 0.01,
        maxDepth = 1)

Figure 2: The Voronoi Tessellation for layer 1 (map A) shown for the 440 cells in the dataset ’computers’

Heat Maps

We will now overlay all the features as heatmap over the Voronoi Tessellation plot for better visualization and identification of patterns, trends, and variations in the data.

Let’s have a look at the function hvtHmap that we will use to overlay features as heatmap.

hvtHmap(hvt.results, dataset, child.level, hmap.cols, color.vec ,line.width, palette.color = 6)

hvt.results - A list of results obtained from the HVT function (map_A).
dataset - A dataframe containing the variables to overlay as a heatmap. The user can pass an external dataset or the dataset that was used to perform hierarchical vector quantization. The dataset should have the same number of points as the dataset used to perform hierarchical Vector Quantization in the HVT function.
child.level - A number indicating the level for which the heat map is to be plotted.
hmap.cols - The column number of column name from the dataset indicating the variables for which the heat map is to be plotted. To plot the quantization error as heatmap, pass 'quant_error'. Similarly to plot the no of points in each cell as heatmap, pass 'no_of_points' as a parameter.
color.vec - A color vector such that length(color.vec) = child.level, let say if the child.level is 2 then 2 color vector should be provided for each level. (default = NULL).
line.width - A line width vector such that length(line.width) = child.level, let say if the child.level is 2 then 2 line width vector should be provided for each level (default = NULL).
palette.color - A number indicating the heat map color palette. 1 - rainbow, 2 - heat.colors, 3 - terrain.colors, 4 - topo.colors, 5 - cm.colors, 6 - BlCyGrYlRd (Blue,Cyan,Green,Yellow,Red) color (default = 6).
show.points - A boolean indicating whether the centroids should be plotted on the tessellations (default = FALSE).

Now let’s plot the Voronoi Tessellation with the heatmap overlaid for all the features in the torus data for better visualization and interpretation of data patterns and distributions.

The heatmaps displayed below provides a visual representation of the spatial characteristics of the computers data, allowing us to observe patterns and trends in the distribution of each of the features (n,price,speed,hd,ram,screen,ads). The sheer green shades highlight regions with higher values in each of the heatmaps, while the indigo shades indicate areas with the lowest values in each of the heatmaps. By analyzing these heatmaps, we can gain insights into the variations and relationships between each of these features within the computers data.


  hvtHmap(
  map_A,
  trainComputers,
  child.level = 1,
  hmap.cols = "n",
  line.width = c(0.2),
  color.vec = c("#141B41"),
  palette.color = 6,
  centroid.size = 0.1,
  show.points = T,
  quant.error.hmap = 0.2,
  n_cells.hmap = 440,
)

Figure 3: The Voronoi Tessellation with the heat map overlaid for No. of entities in each cell


  hvtHmap(
  map_A,
  trainComputers,
  child.level = 1,
  hmap.cols = "price",
  line.width = c(0.2),
  color.vec = c("#141B41"),
  palette.color = 6,
  centroid.size = 0.1,
  show.points = T,
  quant.error.hmap = 0.2,
  n_cells.hmap = 440,
)

Figure 4: The Voronoi Tessellation with the heat map overlaid for variable ’price’ in the ’computers’ dataset


  hvtHmap(
  map_A,
  trainComputers,
  child.level = 1,
  hmap.cols = "speed",
  line.width = c(0.2),
  color.vec = c("#141B41"),
  palette.color = 6,
  centroid.size = 0.1,
  show.points = T,
  quant.error.hmap = 0.2,
  n_cells.hmap = 440,
)

Figure 5: The Voronoi Tessellation with the heat map overlaid for variable ’speed’ in the ’computers’ dataset


  hvtHmap(
  map_A,
  trainComputers,
  child.level = 1,
  hmap.cols = "hd",
  line.width = c(0.2),
  color.vec = c("#141B41"),
  palette.color = 6,
  centroid.size = 0.1,
  show.points = T,
  quant.error.hmap = 0.2,
  n_cells.hmap = 440,
)

Figure 6: The Voronoi Tessellation with the heat map overlaid for variable ’hd’ in the ’computers’ dataset


  hvtHmap(
  map_A,
  trainComputers,
  child.level = 1,
  hmap.cols = "ram",
  line.width = c(0.2),
  color.vec = c("#141B41"),
  palette.color = 6,
  centroid.size = 0.1,
  show.points = T,
  quant.error.hmap = 0.2,
  n_cells.hmap = 440,
)

Figure 7: The Voronoi Tessellation with the heat map overlaid for variable ’ram’ in the ’computers’ dataset


  hvtHmap(
  map_A,
  trainComputers,
  child.level = 1,
  hmap.cols = "screen",
  line.width = c(0.2),
  color.vec = c("#141B41"),
  palette.color = 6,
  centroid.size = 0.1,
  show.points = T,
  quant.error.hmap = 0.2,
  n_cells.hmap = 440,
)

Figure 8: The Voronoi Tessellation with the heat map overlaid for variable ’screen’ in the ’computers’ dataset


  hvtHmap(
  map_A,
  trainComputers,
  child.level = 1,
  hmap.cols = "ads",
  line.width = c(0.2),
  color.vec = c("#141B41"),
  palette.color = 6,
  centroid.size = 0.1,
  show.points = T,
  quant.error.hmap = 0.2,
  n_cells.hmap = 440,
)

Figure 9: The Voronoi Tessellation with the heat map overlaid for variable ’ads’ in the ’computers’ dataset

4 Map B : Compressed Novelty Map

Let us try to visualize the Map B from the flow diagram below.

Figure 10: Flow map with highlighted bounding box in red around map B

In this section, we will manually figure out the novelty cells from the plotted map A and store it in identified_Novelty_cells variable.

Note: For manual selecting the novelty cells from map A, one can enhance its interactivity by adding plotly elements to the code. This will transform map A into an interactive plot, allowing users to actively engage with the data. By hovering over the centroids of the cells, a tag containing segment child information will be displayed. Users can explore the map by hovering over different cells and selectively choose the novelty cells they wish to consider. Added an image for reference.

Figure 11: Manually selecting novelty cells

The removeNovelty function removes the identified novelty cell(s) from the training dataset (containing 5007 datapoints) and stores those records separately.

It takes input as the cell number (Segment.Child) of the manually identified novelty cell(s) and the compressed HVT map (map A) with 440 cells. It returns a list of two items: dataset with novelty records, and a subset of the dataset without the novelty records.

identified_Novelty_cells <<- c(73,321,332,338,435)   #73,321,332,338,435
output_list <- removeNovelty(identified_Novelty_cells, map_A)

[1] “The following cell(s) have been removed as novelties from the dataset: 73 321 332 338 435”

data_with_novelty <- output_list[[1]]
dataset_without_novelty <- output_list[[2]]

Let’s have a look at the data with novelties(containing 24 records). For the sake of brevity, we will only show the first 10 rows.

novelty_data <- data_with_novelty
novelty_data$Row.No <- row.names(novelty_data)
novelty_data <- novelty_data %>% dplyr::select("Row.No","Cell.ID","Cell.Number","price","speed","hd","ram","screen","ads")
colnames(novelty_data) <- c("Row.No","Cell.ID","Segment.Child","price","speed","hd","ram","screen","ads")
novelty_data %>% head(100) %>% 
  as.data.frame() %>%
  Table(scroll = T, limit = 20)

Row.No	Cell.ID	Segment.Child	price	speed	hd	ram	screen	ads
1	429	73	3.0762240	0.6794579	0.0421969	4.2031619	0.4307274	0.7120258
2	438	321	2.6449847	0.6794579	6.5710368	1.3676416	0.4307274	0.6851382
3	438	321	1.6578103	2.2969425	6.5710368	1.3676416	0.4307274	-1.2507722
4	439	332	0.9130997	0.6794579	4.6232922	2.7854017	0.4307274	-2.4607161
5	439	332	1.8569770	1.1076156	4.6232922	4.2031619	2.6404120	-2.4607161
6	439	332	1.5192595	2.2969425	4.6232922	4.2031619	0.4307274	-2.4607161
7	439	332	1.4482522	1.1076156	4.6232922	4.2031619	0.4307274	-2.4607161
8	439	332	1.8569770	1.1076156	4.6232922	4.2031619	2.6404120	-2.4607161
9	439	332	1.1555636	2.2969425	4.6232922	2.7854017	0.4307274	-2.4607161
10	439	332	1.7773103	1.1076156	4.6232922	4.2031619	0.4307274	-2.4607161
11	439	332	1.3460710	0.6794579	4.6232922	4.2031619	0.4307274	-2.4607161
12	439	332	1.4482522	1.1076156	4.6232922	4.2031619	0.4307274	-2.4607161
13	218	338	-1.4959522	0.6794579	0.4473277	-0.7589986	-0.6741149	-2.2993903
14	218	338	-1.5115391	0.6794579	0.4473277	-0.7589986	-0.6741149	-1.9767386
15	218	338	-1.1668940	0.6794579	0.4473277	-0.7589986	-0.6741149	-2.2859465
16	218	338	-1.4959522	0.6794579	0.4473277	-0.7589986	-0.6741149	-2.4472723
17	218	338	-1.5981334	0.6794579	0.4473277	-0.7589986	-0.6741149	-2.2859465
18	218	338	-1.1668940	0.6794579	0.4473277	-0.7589986	-0.6741149	-2.2993903
19	218	338	-1.1668940	0.6794579	0.4473277	-0.7589986	-0.6741149	-2.4472723
20	218	338	-1.3227637	0.6794579	0.4473277	-0.7589986	-0.6741149	-1.9767386

4.1 Voronoi Tessellation with highlighted novelty cell

The plotCells function is used to plot the Voronoi tessellation using the compressed HVT map (map A) containing 440 cells and highlights the identified novelty cell(s) i.e 5 cells (containing 24 records) in red on the map.

plotCells(identified_Novelty_cells, map_A,line.width = c(0.4),centroid.size = 0.01)

Figure 12: The Voronoi Tessellation constructed using the compressed HVT map (map A) with the novelty cell(s) highlighted in red

We pass the dataframe with novelty records (24 records) to HVT function along with other model parameters mentioned below to generate map B (layer2)

Model Parameters

Number of Cells at each Level = 12
Maximum Depth = 1
Quantization Error Threshold = 0.2
Error Metric = Max
Distance Metric = Manhattan

colnames(data_with_novelty) <- c("Cell.ID","Segment.Child","price","speed","hd","ram","screen","ads")
dataset_with_novelty <- data_with_novelty[,-1:-2]
map_B <- list()
mapA_scale_summary = map_A[[3]]$scale_summary
map_B <- muHVT::HVT(dataset_with_novelty,
                  n_cells = 12 ,   #6
                  depth = 1,
                  quant.err = 0.2,
                  projection.scale = 10,
                  normalize = F,
                  distance_metric = "L1_Norm",
                  error_metric = "max",
                  quant_method = "kmeans",
                  diagnose = F
                  )

The datatable displayed below is the summary from map B (layer 2) showing Cell.ID, Centroids and Quantization Error for each of the 12 cells.

summaryTable(map_B[[3]]$summary,scroll = T,limit = 500)

Segment.Level	Segment.Parent	Segment.Child	n	Cell.ID	Quant.Error	price	speed	hd	ram	screen	ads
1	1	1	1	6	0	-1.08	0.68	0.45	-0.76	-0.67	-1.98
1	1	2	1	3	0	-1.51	0.68	0.45	-0.76	-0.67	-1.98
1	1	3	2	1	0.01	-1.55	-0.08	0.45	-0.76	-0.67	-1.98
1	1	4	2	11	0	1.86	1.11	4.62	4.20	2.64	-2.46
1	1	5	1	7	0	3.08	0.68	0.04	4.20	0.43	0.71
1	1	6	5	8	0.31	1.39	0.94	4.62	3.92	0.43	-2.46
1	1	7	1	12	0	5.51	0.68	3.07	4.20	2.64	0.50
1	1	8	2	9	0.15	1.34	2.30	4.62	3.49	0.43	-2.46
1	1	9	1	4	0	-1.32	0.68	0.45	-0.76	-0.67	-1.98
1	1	10	3	2	0.02	-1.53	0.68	0.45	-0.76	-0.67	-2.34
1	1	11	2	10	0.38	2.15	1.49	6.57	1.37	0.43	-0.28
1	1	12	3	5	0.02	-1.17	0.68	0.45	-0.76	-0.67	-2.34

Now let’s check the compression summary for HVT (map B). The table below shows no of cells, no of cells having quantization error below threshold and percentage of cells having quantization error below threshold for each level.

mapB_compression_summary <- map_B[[3]]$compression_summary %>%  dplyr::mutate_if(is.numeric, funs(round(.,4)))
compressionSummaryTable(mapB_compression_summary)

segmentLevel	noOfCells	noOfCellsBelowQuantizationError	percentOfCellsBelowQuantizationErrorThreshold	parameters
1	12	10	0.83	n_cells: 12 quant.err: 0.2 distance_metric: L1_Norm error_metric: max quant_method: kmeans

As it can be seen from the table above, 83% of the cells have hit the quantization threshold error.Since we are successfully able to attain the desired compression percentage, so we will not further subdivide the cells

5 Map C : Compressed Map without Novelty

Let us try to visualize the compressed Map C from the flow diagram below.

Figure 13:Flow map with highlighted bounding box in red around compressed map C

5.0.1 Iteration 1:

With the Novelties removed, we construct another hierarchical Voronoi tessellation map C layer 2 on the dataset without Novelty (containing 4986 records) and below mentioned model parameters.

Model Parameters

Number of Cells at each Level = 10
Maximum Depth = 2
Quantization Error Threshold = 0.2
Error Metric = Max
Distance Metric = Manhattan

map_C <- list()
mapA_scale_summary = map_A[[3]]$scale_summary
map_C <- muHVT::HVT(dataset_without_novelty,
                  n_cells = 10,
                  depth = 2,
                  quant.err = 0.2,
                  projection.scale = 10,
                  normalize = F,
                  distance_metric = "L1_Norm",
                  error_metric = "max",
                  quant_method = "kmeans",
                  diagnose = F,
                  scale_summary = mapA_scale_summary)

Now let’s check the compression summary for HVT (map C) where n_cell was set to 10. The table below shows no of cells, no of cells having quantization error below threshold and percentage of cells having quantization error below threshold for each level.

mapC_compression_summary <- map_C[[3]]$compression_summary %>%  dplyr::mutate_if(is.numeric, funs(round(.,4)))
compressionSummaryTable(mapC_compression_summary)

segmentLevel	noOfCells	noOfCellsBelowQuantizationError	percentOfCellsBelowQuantizationErrorThreshold	parameters
1	10	0	0	n_cells: 10 quant.err: 0.2 distance_metric: L1_Norm error_metric: max quant_method: kmeans
2	100	7	0.07	n_cells: 10 quant.err: 0.2 distance_metric: L1_Norm error_metric: max quant_method: kmeans

As it can be seen from the table above, 0% of the cells have hit the quantization threshold error in level 1 and 7% of the cells have hit the quantization threshold error in level 2

5.0.2 Iteration 2:

Since, we are yet to achive atleast 80% compression at depth 2. Let’s try to compress again using the below mentioned set of model parameters and the dataset without novelty (containing 4983 records).

Model Parameters

Number of Cells at each Level = 23
Maximum Depth = 2
Quantization Error Threshold = 0.2
Error Metric = Max
Distance Metric = Manhattan

map_C <- list()
map_C <- muHVT::HVT(dataset_without_novelty,
                  n_cells = 23,    #23
                  depth = 2,
                  quant.err = 0.2,
                  projection.scale = 10,
                  normalize = F,
                  distance_metric = "L1_Norm",
                  error_metric = "max",
                  quant_method = "kmeans",
                  diagnose = F,
                  scale_summary = mapA_scale_summary)

The datatable displayed below is the summary from map C (layer2). showing Cell.ID, Centroids and Quantization Error for each of the 531 cells.

summaryTable(map_C[[3]]$summary,scroll = T,limit = 500)

Segment.Level	Segment.Parent	Segment.Child	n	Cell.ID	Quant.Error	price	speed	hd	ram	screen	ads
1	1	1	391	512	0.56	-1.27	-1.04	-0.91	-0.83	-0.59	0.86
1	1	2	105	96	1.02	2.08	0.75	0.11	0.71	2.64	0.56
1	1	3	190	55	1.37	1.48	0.02	2.32	2.63	0.12	-0.22
1	1	4	86	15	0.94	0.87	1.27	2.61	2.57	1.33	-1.76
1	1	5	257	326	0.49	0.41	0.45	-0.08	-0.20	-0.67	0.66
1	1	6	116	201	0.77	1.57	0.45	-0.24	0.27	-0.30	-1.30
1	1	7	235	228	0.58	0.85	-0.82	0.42	1.37	-0.47	0.52
1	1	8	149	185	0.84	-0.79	1.73	0.76	-0.22	-0.28	-1.75
1	1	9	353	306	0.69	-0.77	0.55	0.28	-0.22	-0.17	-0.79
1	1	10	234	297	0.54	0.25	0.50	-0.11	-0.16	0.43	0.66
1	1	11	330	478	0.56	-1.18	-0.79	-0.70	-0.76	-0.52	-0.69
1	1	12	373	434	0.6	-0.50	0.40	-0.84	-0.84	-0.56	0.66
1	1	13	209	147	0.81	1.32	0.99	0.36	1.37	-0.01	0.70
1	1	14	337	471	0.36	-0.51	-0.97	-0.87	-0.75	-0.67	0.57
1	1	15	283	404	0.71	0.06	-0.40	-0.78	-0.40	-0.42	-1.42
1	1	16	168	142	0.85	0.13	0.66	0.48	-0.02	2.64	-0.97
1	1	17	285	384	0.53	-0.04	-0.96	0.05	-0.12	-0.65	0.54
1	1	18	118	301	0.75	0.35	2.30	-0.13	-0.29	-0.28	0.82
1	1	19	256	414	0.47	-0.47	-0.84	-0.43	-0.48	0.43	0.60
1	1	20	78	57	1	0.18	1.67	2.05	1.31	0.39	-1.97
1	1	21	171	360	0.64	0.24	-0.46	-0.37	-0.41	2.64	0.59
1	1	22	170	130	1.28	0.28	-0.01	1.64	0.99	0.21	-0.62
1	1	23	89	219	0.88	1.98	0.59	0.20	-0.20	0.12	0.58
2	1	1	19	528	0.09	-1.31	-1.17	-1.19	-1.11	-0.67	0.99
2	1	2	18	479	0.31	-1.42	-0.87	-0.21	-0.72	-0.67	0.53
2	1	3	28	521	0.1	-1.47	-1.22	-1.11	-0.76	-0.67	0.89
2	1	4	10	530	0.14	-1.84	-1.04	-1.20	-1.11	-0.67	0.79
2	1	5	27	519	0.1	-1.20	-1.09	-1.19	-1.11	-0.67	0.50
2	1	6	13	524	0.18	-1.36	-1.10	-0.99	-0.87	0.43	1.36
2	1	7	5	523	0.04	-1.19	-1.27	-0.78	-0.76	-0.67	1.57
2	1	8	23	494	0.06	-1.18	-0.89	-0.78	-0.76	-0.67	0.72
2	1	9	27	514	0.14	-1.35	-1.27	-1.08	-0.76	-0.67	0.39
2	1	10	35	510	0.1	-1.08	-1.27	-0.88	-0.76	-0.67	0.90
2	1	11	6	529	0.15	-1.22	-0.62	-1.19	-1.11	-0.67	1.50
2	1	12	10	513	0.07	-0.95	-0.89	-0.85	-0.76	-0.67	1.57
2	1	13	10	517	0.22	-1.70	-1.19	-0.73	-0.83	-0.67	0.57
2	1	14	11	472	0.17	-1.19	-1.13	-0.33	-0.05	-0.67	0.97
2	1	15	11	507	0.19	-1.00	-0.93	-1.17	-0.63	-0.67	0.97
2	1	16	7	531	0.07	-1.58	-1.27	-1.18	-0.96	-0.67	1.57
2	1	17	26	499	0.09	-1.31	-0.89	-0.92	-0.76	-0.67	0.36
2	1	18	23	515	0.07	-0.99	-0.89	-1.19	-1.11	-0.67	0.92
2	1	19	13	520	0.14	-1.56	-0.98	-0.74	-0.76	-0.67	1.34
2	1	20	15	489	0.12	-1.05	-0.89	-0.26	-0.76	-0.67	1.31
2	1	21	16	503	0.18	-1.48	-0.79	-0.73	-0.76	-0.67	0.76
2	1	22	15	518	0.26	-1.37	-1.07	-1.09	-1.07	0.43	0.66
2	1	23	23	500	0.07	-1.03	-0.89	-0.82	-0.76	-0.67	1.06
2	2	1	4	108	0.12	2.31	0.68	-0.12	-0.05	2.64	1.31
2	2	2	3	118	0.11	2.53	0.68	-0.47	-0.76	2.64	0.36
2	2	3	7	99	0.21	1.06	0.80	0.29	1.37	2.64	0.35
2	2	4	2	89	0.06	1.09	2.30	0.25	-0.05	2.64	1.57
2	2	5	7	59	0.13	3.21	0.68	-0.27	1.37	2.64	0.53
2	2	6	7	88	0.11	1.85	0.68	0.16	1.37	2.64	0.85
2	2	7	2	145	0.11	1.14	0.68	0.10	-0.05	2.64	1.36
2	2	8	3	38	0.11	3.32	0.68	-0.27	1.37	2.64	-0.78
2	2	9	6	100	0.17	2.86	0.68	0.10	-0.05	2.64	0.48
2	2	10	2	24	0.11	3.50	2.30	1.23	-0.05	2.64	-0.23
2	2	11	2	12	0.38	4.64	0.68	1.36	0.66	2.64	0.37
2	2	12	6	56	0.25	1.52	2.30	0.32	1.37	2.64	0.77
2	2	13	4	50	0.34	1.64	0.49	1.90	1.37	2.64	0.14
2	2	14	13	76	0.22	2.42	0.68	0.03	1.37	2.64	0.53
2	2	15	4	103	0.12	1.08	2.30	0.14	-0.05	2.64	0.52
2	2	16	11	167	0.13	1.23	0.68	-0.20	-0.05	2.64	0.59
2	2	17	1	107	0	1.99	-0.08	0.49	-0.05	2.64	-0.62
2	2	18	4	84	0.15	1.52	0.68	0.34	1.37	2.64	1.36
2	2	19	5	169	0.17	1.81	-0.08	-0.29	-0.19	2.64	0.99
2	2	20	4	70	0.11	2.69	-0.89	-0.27	1.37	2.64	0.69
2	2	21	4	122	0.11	1.99	0.68	0.22	-0.05	2.64	0.57
2	2	22	3	60	0.12	2.74	-0.89	-0.27	1.37	2.64	-0.78
2	2	23	1	195	0	1.63	0.68	-0.95	-0.76	2.64	0.69
2	3	1	5	39	0.04	1.54	-0.08	2.29	2.79	0.43	-0.81
2	3	2	3	9	0.05	1.71	-0.89	2.29	2.79	2.64	-0.55
2	3	3	10	51	0.07	1.10	-0.08	2.29	2.79	0.43	-0.56
2	3	4	5	32	0.39	3.74	-0.10	2.60	1.37	-0.67	0.96
2	3	5	3	19	0.02	2.16	2.30	2.29	2.79	-0.67	0.04
2	3	6	1	20	0	2.03	2.30	2.29	2.79	0.43	0.35
2	3	7	16	49	0.18	1.49	-0.89	2.29	2.79	0.43	-0.06
2	3	8	7	40	0.09	1.80	-0.08	2.29	2.79	0.43	-0.26
2	3	9	2	54	0.05	2.90	0.68	3.73	-0.05	-0.67	0.69
2	3	10	1	91	0	1.16	0.68	2.29	1.37	-0.67	0.04
2	3	11	7	46	0.05	1.16	0.68	2.29	2.79	0.43	-0.49
2	3	12	4	77	0.12	1.66	0.68	2.44	1.37	0.43	0.80
2	3	13	7	37	0.08	1.63	0.68	2.29	2.79	0.43	-0.73
2	3	14	12	53	0.1	1.69	0.68	2.29	2.79	-0.67	0.38
2	3	15	2	43	0.04	3.07	0.68	2.29	1.37	-0.67	-0.87
2	3	16	5	23	0.04	2.06	2.30	2.29	2.79	-0.67	0.35
2	3	17	12	45	0.06	0.92	0.68	2.29	2.79	0.43	-0.86
2	3	18	5	82	0.13	1.35	0.68	2.47	1.37	0.43	0.11
2	3	19	5	17	0.04	2.23	2.30	2.29	2.79	-0.67	0.69
2	3	20	24	61	0.12	1.30	-0.89	2.29	2.79	-0.67	0.33
2	3	21	9	36	0.18	2.07	0.68	2.29	2.79	0.43	-0.03
2	3	22	13	52	0.11	0.65	-0.08	2.29	2.79	0.43	-1.03
2	3	23	32	48	0.13	1.15	-0.89	2.29	2.79	0.43	-0.66
2	4	1	5	7	0.11	0.51	2.30	2.05	1.37	2.64	-2.33
2	4	2	8	18	0.07	0.52	0.68	3.07	2.79	0.43	-2.36
2	4	3	6	41	0.05	0.79	0.68	2.29	2.79	0.43	-1.24
2	4	4	2	3	0	1.08	2.30	3.07	2.79	0.43	-2.46
2	4	5	3	8	0.13	1.91	0.43	2.29	2.79	2.64	-0.55
2	4	6	1	11	0	0.01	1.11	3.07	2.79	0.43	-2.45
2	4	7	3	26	0.03	0.73	-0.08	3.07	2.79	0.43	-1.98
2	4	8	1	4	0	0.99	-0.08	3.07	2.79	2.64	-1.98
2	4	9	3	2	0.05	1.48	2.30	2.29	2.79	2.64	-1.08
2	4	10	2	14	0.02	0.81	0.68	3.07	2.79	0.43	-2.46
2	4	11	1	6	0	0.74	2.30	3.07	2.79	0.43	-1.98
2	4	12	2	16	0.02	0.89	1.11	3.07	2.79	0.43	-1.98
2	4	13	2	29	0.04	0.84	2.30	1.70	1.37	2.64	-1.02
2	4	14	6	5	0.03	0.74	2.30	3.07	2.79	0.43	-2.40
2	4	15	7	1	0.23	1.03	1.16	3.07	2.79	2.64	-2.34
2	4	16	5	25	0.02	1.02	2.30	2.29	2.79	0.43	-1.23
2	4	17	6	22	0.25	0.85	-0.22	2.29	2.79	2.64	-0.97
2	4	18	2	13	0.05	1.21	0.68	2.29	2.79	2.64	-1.10
2	4	19	5	30	0.11	0.32	0.68	2.17	1.37	2.64	-2.29
2	4	20	6	10	0.04	0.69	1.11	3.07	2.79	0.43	-2.32
2	4	21	1	34	0	0.30	-0.08	2.29	1.37	2.64	-1.98
2	4	22	6	21	0.06	1.46	2.30	2.29	2.79	0.43	-1.01
2	4	23	3	28	0.01	1.00	2.30	2.29	2.79	0.43	-0.79
2	5	1	24	300	0.13	0.57	0.68	0.13	-0.05	-0.67	0.72
2	5	2	9	332	0.08	-0.44	0.68	-0.04	-0.05	-0.67	0.21
2	5	3	5	310	0.12	0.37	-0.08	0.29	-0.05	-0.67	-0.14
2	5	4	21	312	0.17	0.35	0.86	0.11	-0.05	-0.67	1.39
2	5	5	6	311	0.06	-0.28	0.68	0.45	-0.05	-0.67	0.30
2	5	6	8	287	0.15	0.45	0.68	0.16	-0.05	-0.67	-0.20
2	5	7	5	305	0.06	-0.07	0.68	0.45	-0.05	-0.67	0.48
2	5	8	7	333	0.12	0.31	0.68	-0.57	-0.05	-0.67	0.57
2	5	9	12	319	0.06	-0.12	0.68	0.04	-0.05	-0.67	0.14
2	5	10	13	358	0.15	-0.04	-0.08	0.00	-0.05	-0.67	0.83
2	5	11	11	371	0.16	0.41	0.68	-0.40	-0.76	-0.67	0.94
2	5	12	7	314	0.16	1.02	0.68	-0.39	-0.15	-0.67	1.12
2	5	13	17	363	0.2	0.66	0.63	-0.69	-0.76	-0.67	0.15
2	5	14	15	278	0.11	1.06	0.68	0.06	-0.05	-0.67	0.76
2	5	15	8	356	0.16	0.13	0.79	-0.13	-0.76	-0.67	0.38
2	5	16	11	275	0.19	1.06	0.68	-0.09	-0.05	-0.67	0.19
2	5	17	23	334	0.13	0.51	-0.08	0.01	-0.05	-0.67	0.91
2	5	18	17	324	0.11	0.69	-0.08	-0.08	-0.05	-0.67	0.46
2	5	19	12	402	0.15	0.15	-0.08	-0.20	-0.76	-0.67	0.94
2	5	20	7	386	0.14	1.08	-0.08	-0.62	-0.76	-0.67	0.63
2	5	21	12	336	0.2	-0.17	0.68	-0.04	-0.05	-0.67	0.86
2	5	22	7	364	0.13	0.24	-0.08	-0.05	-0.05	-0.67	1.57
2	5	23	0	NA	NA	NA	NA	NA	NA	NA	NA
2	6	1	6	184	0.1	2.46	0.68	0.21	-0.05	-0.67	-0.87
2	6	2	9	133	0.29	1.43	0.51	-0.44	1.37	0.43	-1.15
2	6	3	2	233	0.08	1.08	0.68	0.47	-0.05	-0.67	-0.71
2	6	4	9	247	0.22	0.90	0.59	-0.69	-0.13	0.43	-1.39
2	6	5	2	194	0.08	2.30	0.30	-0.32	-0.05	-0.67	-1.71
2	6	6	8	238	0.26	1.04	0.58	-0.29	-0.14	0.43	-0.77
2	6	7	9	127	0.06	2.98	0.68	0.28	-0.05	-0.67	-1.67
2	6	8	4	165	0.11	1.26	-0.08	-0.07	1.37	-0.67	-1.37
2	6	9	5	124	0.19	1.76	0.53	-0.29	1.37	-0.67	-1.66
2	6	10	1	101	0	3.77	0.68	0.15	-0.05	-0.67	-1.72
2	6	11	5	292	0.22	1.44	0.53	-0.77	-0.33	-0.67	-1.67
2	6	12	1	365	0	1.35	-0.08	-0.67	-0.76	-0.67	-0.62
2	6	13	4	149	0.06	1.43	0.68	0.15	1.37	-0.67	-0.87
2	6	14	10	197	0.2	1.57	0.68	-0.47	-0.33	0.43	-1.64
2	6	15	3	159	0.2	1.48	2.30	0.28	-0.05	-0.67	-0.87
2	6	16	3	280	0.1	0.85	-0.08	0.22	-0.05	-0.67	-0.68
2	6	17	9	191	0.15	1.09	-0.93	-0.29	1.37	-0.67	-1.62
2	6	18	4	140	0.08	3.03	-0.08	0.15	-0.05	-0.67	-1.65
2	6	19	7	294	0.05	0.73	0.68	-0.69	-0.05	-0.67	-1.60
2	6	20	3	112	0.09	2.96	0.68	0.12	-0.05	0.43	-1.72
2	6	21	2	270	0.04	1.61	0.68	-0.71	-0.05	-0.67	-0.87
2	6	22	8	279	0.09	0.84	0.68	-0.36	-0.05	-0.67	-0.84
2	6	23	2	237	0.08	2.30	-0.49	0.15	-0.05	-0.67	-1.12
2	7	1	8	210	0.16	0.51	-1.18	0.46	1.37	0.43	1.10
2	7	2	16	231	0.12	1.01	-0.91	0.35	1.37	-0.67	0.40
2	7	3	12	211	0.1	1.39	-0.89	0.37	1.37	-0.67	0.29
2	7	4	8	209	0.06	0.35	-0.89	1.20	1.37	-0.67	0.35
2	7	5	5	263	0.05	0.58	-0.89	0.45	1.37	-0.67	1.57
2	7	6	12	202	0.18	0.49	-1.02	0.55	1.37	0.43	0.36
2	7	7	14	264	0.08	0.43	-0.89	0.45	1.37	-0.67	0.64
2	7	8	2	166	0.09	0.99	-0.08	0.45	1.37	0.43	0.26
2	7	9	11	216	0.14	0.82	-1.03	0.15	1.37	-0.67	-0.85
2	7	10	20	220	0.09	1.20	-0.91	0.45	1.37	-0.67	0.84
2	7	11	9	265	0.07	0.48	-1.27	0.45	1.37	-0.67	0.66
2	7	12	14	190	0.21	1.09	-0.89	0.28	1.37	0.43	0.63
2	7	13	9	222	0.09	0.82	-1.06	0.45	1.37	-0.67	-0.07
2	7	14	7	168	0.2	0.97	-1.00	0.03	1.37	0.43	-0.83
2	7	15	9	204	0.2	0.72	-0.08	0.45	1.37	-0.55	1.43
2	7	16	17	243	0.09	0.82	-0.98	0.46	1.37	-0.67	0.95
2	7	17	7	262	0.04	0.22	-0.89	0.45	1.37	-0.67	0.04
2	7	18	7	285	0.07	0.28	-1.22	0.45	1.37	-0.67	1.12
2	7	19	6	179	0.12	1.31	-0.08	0.35	1.37	-0.67	-0.26
2	7	20	17	189	0.14	1.26	-0.08	0.46	1.37	-0.67	0.84
2	7	21	3	316	0.02	0.10	-1.27	0.45	1.37	-0.67	1.57
2	7	22	11	183	0.11	1.44	-0.08	0.34	1.37	-0.67	0.42
2	7	23	11	251	0.09	0.72	-1.24	0.29	1.37	-0.67	0.36
2	8	1	5	116	0.08	-0.74	0.68	1.70	-0.05	0.43	-2.35
2	8	2	2	282	0	-1.43	0.68	0.45	-0.76	0.43	-2.29
2	8	3	8	182	0.09	-0.47	2.30	0.49	-0.05	0.43	-0.85
2	8	4	10	236	0.19	-0.61	2.30	0.49	-0.05	-0.67	-1.01
2	8	5	13	87	0.15	-0.66	2.30	1.70	-0.05	-0.16	-2.28
2	8	6	4	117	0.13	-1.29	0.49	2.29	-0.76	-0.67	-2.17
2	8	7	2	64	0.02	-1.12	2.30	2.29	-0.76	-0.67	-2.37
2	8	8	3	104	0.06	-0.17	2.30	2.29	-0.05	-0.67	-0.98
2	8	9	4	170	0.08	-0.90	1.11	1.35	-0.05	0.43	-1.21
2	8	10	7	146	0.07	-0.91	2.30	0.47	-0.05	-0.67	-2.34
2	8	11	12	409	0.11	-0.78	2.30	-0.33	-0.76	-0.67	-1.03
2	8	12	7	241	0.1	-0.19	2.30	0.33	-0.05	-0.67	-0.89
2	8	13	4	258	0.09	0.04	2.30	-0.08	-0.05	-0.67	-1.04
2	8	14	9	330	0.09	-1.17	2.30	0.45	-0.76	-0.67	-2.26
2	8	15	6	212	0.13	-0.74	0.68	0.30	-0.05	0.43	-2.40
2	8	16	7	175	0.07	-0.53	2.30	0.49	-0.05	0.43	-1.23
2	8	17	4	109	0.04	-0.38	2.30	1.70	-0.05	0.43	-1.05
2	8	18	10	144	0.09	-0.89	0.68	1.70	-0.05	-0.67	-2.20
2	8	19	1	283	0	-1.59	0.68	-0.19	-0.05	0.43	-2.29
2	8	20	7	123	0.17	-0.94	2.30	0.46	-0.35	0.43	-2.27
2	8	21	3	329	0.06	-0.86	2.30	-0.29	-0.76	0.43	-0.98
2	8	22	21	277	0.11	-1.16	0.68	0.48	-0.05	-0.67	-2.25
2	8	23	0	NA	NA	NA	NA	NA	NA	NA	NA
2	9	1	33	331	0.22	-0.57	-0.08	0.41	-0.05	-0.67	-0.71
2	9	2	10	368	0.19	-0.75	0.68	-0.60	-0.76	0.43	-0.42
2	9	3	13	423	0.19	-1.02	0.68	-0.69	-0.70	-0.67	-0.83
2	9	4	8	335	0.2	-0.08	0.68	-0.49	-0.23	-0.67	-0.86
2	9	5	15	377	0.21	-1.31	-0.08	0.30	-0.76	0.43	-0.98
2	9	6	8	224	0.04	-0.74	1.11	0.50	-0.05	0.43	-1.22
2	9	7	22	261	0.13	-0.22	0.68	0.29	-0.05	0.43	-0.60
2	9	8	14	381	0.28	-0.89	0.57	-0.09	-0.51	-0.67	-0.23
2	9	9	14	257	0.08	-0.64	0.68	0.49	-0.05	0.43	-0.76
2	9	10	13	354	0.27	-1.37	0.33	0.47	-0.27	-0.67	-0.93
2	9	11	9	248	0.16	-1.00	0.68	0.57	-0.05	0.43	-1.22
2	9	12	23	323	0.13	-0.51	0.68	0.02	-0.05	-0.67	-0.46
2	9	13	10	344	0.25	-1.39	0.68	-0.30	-0.48	0.43	-1.23
2	9	14	11	267	0.11	-1.03	0.68	0.41	-0.05	0.43	-0.85
2	9	15	20	422	0.17	-1.43	0.68	-0.23	-0.72	-0.67	-1.02
2	9	16	23	206	0.26	-0.52	0.70	1.25	-0.05	0.43	-0.79
2	9	17	8	304	0.13	-0.86	0.68	-0.12	-0.05	0.43	-0.39
2	9	18	8	240	0.05	-0.72	1.11	0.50	-0.05	0.43	-0.83
2	9	19	32	303	0.35	-0.82	0.68	0.33	0.04	-0.67	-1.07
2	9	20	13	317	0.16	-1.11	0.68	0.34	-0.76	0.43	-0.90
2	9	21	10	308	0.22	-0.75	-0.24	0.33	-0.05	0.43	-0.69
2	9	22	33	296	0.2	-0.39	0.68	0.55	-0.05	-0.67	-0.56
2	9	23	3	196	0.03	-0.83	-0.08	1.70	-0.05	-0.67	-1.98
2	10	1	4	269	0.07	0.51	0.68	-0.55	-0.05	0.43	-0.62
2	10	2	8	327	0.1	-0.43	0.68	-0.12	-0.05	0.43	1.46
2	10	3	23	318	0.15	0.23	-0.08	-0.23	-0.05	0.43	0.69
2	10	4	3	346	0.12	-0.04	0.68	-0.74	-0.76	0.43	-0.31
2	10	5	9	271	0.17	0.14	0.73	0.34	-0.05	0.43	1.57
2	10	6	10	273	0.12	0.92	0.68	-0.54	-0.05	0.43	0.74
2	10	7	9	299	0.11	0.93	-0.08	-0.36	-0.05	0.43	0.66
2	10	8	6	307	0.08	-0.01	0.68	-0.52	-0.05	0.43	0.38
2	10	9	8	289	0.15	0.67	-0.08	-0.27	-0.05	0.43	-0.15
2	10	10	13	325	0.26	0.16	-0.08	0.00	-0.16	0.43	1.23
2	10	11	13	315	0.18	-0.46	0.68	-0.14	-0.05	0.43	0.64
2	10	12	10	259	0.12	0.83	0.68	-0.14	-0.05	0.43	0.32
2	10	13	7	234	0.06	-0.20	0.68	1.23	-0.05	0.43	0.35
2	10	14	12	260	0.16	0.74	0.72	0.08	-0.05	0.43	0.89
2	10	15	8	249	0.12	0.66	0.68	0.48	-0.14	0.43	0.81
2	10	16	13	268	0.09	0.04	0.68	0.49	-0.05	0.43	0.60
2	10	17	11	256	0.11	0.31	0.68	0.24	-0.05	0.43	-0.06
2	10	18	6	342	0.17	0.82	0.30	-0.76	-0.76	0.43	0.64
2	10	19	8	302	0.15	0.22	0.68	-0.33	-0.05	0.43	1.20
2	10	20	12	370	0.24	-0.28	0.75	-0.51	-0.76	0.43	0.84
2	10	21	19	281	0.11	0.29	0.68	-0.07	-0.05	0.43	0.64
2	10	22	9	290	0.13	-0.34	0.68	0.15	-0.05	0.43	0.20
2	10	23	13	351	0.11	0.21	0.68	-0.70	-0.76	0.43	0.66
2	11	1	10	411	0.22	-1.09	-0.93	0.23	-0.12	-0.67	-0.72
2	11	2	14	502	0.14	-1.13	-0.97	-1.01	-0.86	-0.67	-0.09
2	11	3	7	481	0.2	-0.81	-0.08	-1.20	-1.11	-0.36	-0.96
2	11	4	19	516	0.16	-0.95	-0.95	-1.13	-0.91	-0.67	-1.64
2	11	5	14	482	0.12	-1.58	-0.89	-0.16	-0.76	-0.67	-0.68
2	11	6	24	498	0.16	-1.36	-0.94	-0.85	-0.77	-0.67	-0.46
2	11	7	17	527	0.25	-1.29	-1.25	-1.06	-0.84	-0.61	-1.65
2	11	8	23	484	0.15	-1.01	-0.92	-0.84	-0.79	-0.67	-0.72
2	11	9	18	509	0.1	-1.67	-0.91	-0.78	-0.76	-0.67	-0.75
2	11	10	10	435	0.15	-0.94	-0.08	-0.59	-0.69	-0.67	-0.89
2	11	11	19	491	0.25	-1.54	-0.93	-0.50	-0.74	-0.67	-0.11
2	11	12	12	452	0.25	-1.47	-0.76	-0.12	-0.79	0.43	-0.55
2	11	13	8	445	0.17	-1.22	-0.08	-0.43	-0.67	-0.67	-0.19
2	11	14	8	427	0.08	-0.60	-0.89	-0.75	-0.05	-0.67	-0.70
2	11	15	17	466	0.16	-0.52	-0.98	-0.84	-0.76	-0.67	-0.67
2	11	16	17	511	0.16	-1.09	-1.00	-1.06	-0.88	-0.67	-1.12
2	11	17	8	437	0.08	-0.69	-0.08	-0.75	-0.76	-0.67	-0.48
2	11	18	9	465	0.09	-1.33	-0.08	-0.78	-0.76	-0.67	-0.56
2	11	19	10	525	0.18	-1.69	-1.19	-1.13	-0.90	-0.67	-0.23
2	11	20	30	473	0.29	-1.06	-0.87	-0.89	-0.79	0.43	-0.61
2	11	21	6	450	0.1	-1.62	-0.08	-0.06	-0.76	-0.67	-0.70
2	11	22	18	457	0.26	-1.05	-0.89	-0.10	-0.68	-0.67	-0.16
2	11	23	12	453	0.09	-1.43	-0.08	-0.29	-0.76	-0.67	-1.02
2	12	1	25	397	0.2	-0.09	0.68	-0.76	-0.70	-0.67	0.48
2	12	2	13	394	0.18	-0.08	0.68	-0.81	-0.79	-0.67	-0.16
2	12	3	13	413	0.17	0.17	0.68	-1.08	-0.87	-0.67	0.72
2	12	4	21	474	0.12	-0.56	0.68	-1.19	-1.10	-0.67	0.96
2	12	5	15	442	0.11	-0.32	0.68	-1.19	-1.09	-0.67	0.31
2	12	6	12	458	0.26	-0.88	0.68	-0.73	-0.70	-0.67	1.24
2	12	7	17	405	0.25	-0.57	0.68	-0.86	-0.90	0.43	0.44
2	12	8	23	421	0.14	0.08	-0.08	-0.77	-0.76	-0.67	0.62
2	12	9	24	468	0.16	-0.66	-0.08	-1.13	-0.98	-0.67	0.37
2	12	10	6	433	0.13	-0.26	-0.08	-0.91	-0.88	-0.67	-0.11
2	12	11	8	449	0.09	-0.21	0.84	-0.78	-0.76	-0.67	1.57
2	12	12	10	454	0.22	-0.75	0.72	-0.93	-0.94	0.43	1.25
2	12	13	19	428	0.17	-0.83	-0.08	-0.26	-0.68	-0.67	0.55
2	12	14	8	506	0.12	-0.51	1.05	-1.19	-1.11	-0.67	1.36
2	12	15	9	443	0.16	-0.77	-0.08	-0.08	-0.76	-0.67	1.22
2	12	16	21	441	0.19	-0.46	-0.08	-0.80	-0.62	-0.67	0.85
2	12	17	21	436	0.14	-0.85	0.68	-0.87	-0.76	-0.67	0.44
2	12	18	27	492	0.15	-0.84	-0.08	-1.17	-1.05	-0.67	0.90
2	12	19	9	495	0.15	-0.81	-0.08	-0.91	-0.88	-0.67	1.48
2	12	20	19	431	0.24	-0.99	0.68	-0.80	-0.78	-0.67	-0.34
2	12	21	16	387	0.2	-0.62	0.68	-0.11	-0.67	-0.67	0.49
2	12	22	10	477	0.19	-0.79	-0.08	-1.19	-1.11	0.43	0.74
2	12	23	27	415	0.13	-0.11	0.76	-0.76	-0.76	-0.67	1.01
2	13	1	10	138	0.21	0.94	0.68	0.67	1.37	0.43	-0.06
2	13	2	14	131	0.21	2.10	0.68	0.25	1.37	0.43	0.77
2	13	3	4	198	0.02	0.61	0.68	0.45	1.37	-0.67	0.69
2	13	4	2	47	0.19	1.96	1.49	2.29	1.37	0.43	1.36
2	13	5	8	143	0.08	1.28	1.11	0.45	1.37	-0.67	1.36
2	13	6	4	98	0.2	0.98	2.30	0.73	1.37	0.43	0.00
2	13	7	10	155	0.13	1.55	0.68	-0.28	1.37	0.43	0.33
2	13	8	24	151	0.12	1.45	0.68	0.22	1.37	0.43	0.72
2	13	9	5	164	0.11	1.30	-0.08	0.40	1.37	0.43	0.73
2	13	10	12	176	0.12	1.08	0.68	-0.15	1.37	0.43	0.72
2	13	11	10	94	0.13	1.39	2.30	0.44	1.37	0.43	1.23
2	13	12	12	154	0.12	1.75	0.68	0.36	1.37	-0.67	0.29
2	13	13	4	174	0.1	0.56	0.68	0.82	1.37	-0.67	0.19
2	13	14	18	153	0.27	0.89	0.75	0.30	1.37	0.43	1.33
2	13	15	10	172	0.22	0.58	0.77	0.34	1.37	0.43	0.47
2	13	16	8	177	0.08	0.88	0.68	0.45	1.37	-0.67	1.41
2	13	17	2	125	0.09	2.71	0.68	0.34	1.37	-0.67	0.67
2	13	18	8	95	0.07	1.62	2.30	0.45	1.37	-0.67	1.41
2	13	19	7	173	0.07	1.27	0.68	0.45	1.37	-0.67	0.74
2	13	20	7	128	0.1	1.78	0.68	0.38	1.37	0.43	-0.02
2	13	21	16	111	0.2	1.15	2.30	0.59	1.37	-0.67	0.18
2	13	22	10	152	0.11	1.78	0.68	0.46	1.37	-0.67	0.90
2	13	23	4	162	0.07	1.30	0.68	0.46	1.37	-0.67	0.05
2	14	1	46	475	0.08	-0.74	-0.89	-0.78	-0.76	-0.67	0.52
2	14	2	36	469	0.16	-0.24	-0.94	-0.83	-0.76	-0.67	0.94
2	14	3	19	439	0.18	-0.52	-0.95	-0.74	-0.05	-0.67	0.60
2	14	4	13	459	0.15	0.21	-1.04	-0.93	-0.76	-0.67	0.60
2	14	5	24	501	0.14	-0.59	-1.00	-1.16	-0.89	-0.67	0.87
2	14	6	44	480	0.13	-0.63	-0.93	-0.78	-0.76	-0.67	0.98
2	14	7	35	493	0.13	-0.68	-0.91	-1.17	-0.98	-0.67	0.42
2	14	8	19	451	0.1	-0.20	-0.95	-0.74	-0.76	-0.67	-0.06
2	14	9	19	483	0.14	-0.72	-1.03	-0.93	-0.85	-0.67	-0.07
2	14	10	34	488	0.13	-0.61	-1.27	-0.93	-0.76	-0.67	0.54
2	14	11	11	455	0.18	-0.85	-0.89	-0.17	-0.69	-0.67	0.45
2	14	12	37	462	0.1	-0.26	-0.91	-0.85	-0.76	-0.67	0.39
2	14	13	0	NA	NA	NA	NA	NA	NA	NA	NA
2	14	14	0	NA	NA	NA	NA	NA	NA	NA	NA
2	14	15	0	NA	NA	NA	NA	NA	NA	NA	NA
2	14	16	0	NA	NA	NA	NA	NA	NA	NA	NA
2	14	17	0	NA	NA	NA	NA	NA	NA	NA	NA
2	14	18	0	NA	NA	NA	NA	NA	NA	NA	NA
2	14	19	0	NA	NA	NA	NA	NA	NA	NA	NA
2	14	20	0	NA	NA	NA	NA	NA	NA	NA	NA
2	14	21	0	NA	NA	NA	NA	NA	NA	NA	NA
2	14	22	0	NA	NA	NA	NA	NA	NA	NA	NA
2	14	23	0	NA	NA	NA	NA	NA	NA	NA	NA
2	15	1	13	341	0.17	0.19	-0.92	-0.52	-0.05	0.43	-0.93
2	15	2	16	361	0.16	0.24	0.68	-0.91	-0.45	-0.67	-1.62
2	15	3	5	456	0.11	-0.29	-0.89	-0.70	-0.76	-0.67	-1.12
2	15	4	26	461	0.2	-0.35	-0.08	-1.04	-0.81	-0.67	-1.59
2	15	5	16	444	0.3	-0.40	0.68	-1.15	-0.94	-0.61	-1.48
2	15	6	15	486	0.08	-0.50	-0.89	-0.92	-0.76	-0.67	-1.66
2	15	7	5	203	0.2	0.69	-1.12	-0.43	1.37	-0.23	-1.58
2	15	8	9	426	0.33	-0.40	-0.75	-0.77	-0.68	0.43	-1.23
2	15	9	14	369	0.19	0.28	-0.92	-0.38	-0.05	-0.67	-0.90
2	15	10	11	464	0.07	-0.06	-0.89	-0.82	-0.76	-0.67	-1.66
2	15	11	5	460	0.11	0.54	-0.89	-0.88	-0.76	-0.67	-1.70
2	15	12	7	410	0.17	0.51	-0.08	-0.92	-0.76	-0.67	-1.57
2	15	13	17	352	0.15	0.35	-0.89	-0.72	-0.13	0.43	-1.66
2	15	14	11	420	0.08	0.02	-1.03	-0.67	-0.05	-0.67	-1.65
2	15	15	13	396	0.13	0.43	-0.89	-0.71	-0.05	-0.67	-1.63
2	15	16	4	379	0.23	0.75	-0.69	-0.65	-0.76	0.15	-0.67
2	15	17	7	322	0.21	0.47	0.24	-0.72	-0.66	0.43	-1.52
2	15	18	25	343	0.22	0.36	-0.08	-0.63	-0.05	-0.67	-1.53
2	15	19	15	496	0.09	-0.38	-1.04	-1.11	-0.76	-0.67	-1.63
2	15	20	14	380	0.3	0.03	-0.08	-0.55	-0.46	-0.67	-0.82
2	15	21	14	293	0.21	0.50	-0.08	-0.67	-0.05	0.43	-1.14
2	15	22	10	353	0.17	0.20	0.68	-0.81	-0.48	-0.67	-0.92
2	15	23	11	432	0.09	-0.35	-0.89	-0.80	-0.05	-0.67	-1.61
2	16	1	8	58	0.25	0.04	2.30	1.70	-0.05	2.64	-1.20
2	16	2	1	33	0	1.25	2.30	1.20	1.37	2.64	-0.94
2	16	3	13	90	0.39	0.07	2.30	0.48	-0.05	2.64	-0.99
2	16	4	5	230	0.11	0.87	-0.89	-0.67	-0.33	2.64	-1.64
2	16	5	11	163	0.15	-0.13	0.68	0.38	-0.05	2.64	-0.78
2	16	6	4	75	0.04	0.84	-0.89	1.20	1.37	2.64	-0.83
2	16	7	17	207	0.2	-0.62	0.68	0.36	-0.76	2.64	-1.01
2	16	8	20	135	0.14	-0.24	0.98	0.51	-0.05	2.64	-1.10
2	16	9	9	132	0.15	1.33	-0.08	-0.65	-0.29	2.64	-1.52
2	16	10	8	74	0.2	0.95	0.39	1.10	1.37	2.64	-0.65
2	16	11	8	284	0.05	-0.76	-0.08	0.51	-0.76	2.64	-1.16
2	16	12	5	83	0.04	0.78	-0.89	1.20	1.37	2.64	-0.43
2	16	13	5	105	0.07	-0.44	0.68	0.49	-0.05	2.64	-2.23
2	16	14	4	136	0.09	1.24	0.68	-0.64	-0.05	2.64	-0.87
2	16	15	2	106	0.03	1.56	0.68	-0.71	-0.76	2.64	-1.71
2	16	16	9	120	0.06	-0.01	0.68	1.23	-0.05	2.64	-0.72
2	16	17	7	67	0.21	0.47	0.41	1.49	1.37	2.64	-0.97
2	16	18	7	213	0.33	0.07	0.57	-0.21	-0.05	2.64	-0.36
2	16	19	5	160	0.15	0.43	0.68	0.62	-0.05	2.64	0.17
2	16	20	6	320	0.13	-0.58	0.68	-0.26	-0.76	2.64	-0.44
2	16	21	3	85	0.06	0.38	0.68	2.29	-0.05	2.64	-0.61
2	16	22	6	345	0.1	-0.82	-0.08	0.21	-0.76	2.64	-0.79
2	16	23	5	110	0.06	1.39	0.68	-0.67	-0.05	2.64	-1.61
2	17	1	6	440	0.09	-0.58	-1.27	0.12	-0.05	-0.67	1.29
2	17	2	10	416	0.13	-0.58	-0.93	-0.18	-0.05	-0.67	0.64
2	17	3	12	417	0.09	-0.24	-0.92	0.15	-0.05	-0.67	1.57
2	17	4	9	349	0.12	0.29	-0.93	0.23	-0.05	-0.67	-0.11
2	17	5	5	309	0.28	0.52	-0.89	0.35	-0.05	0.43	0.52
2	17	6	16	385	0.13	0.31	-0.89	-0.45	-0.05	-0.67	0.41
2	17	7	23	372	0.09	0.31	-0.91	0.03	-0.05	-0.67	0.86
2	17	8	21	403	0.09	-0.15	-1.27	0.09	-0.05	-0.67	0.85
2	17	9	14	366	0.13	-0.37	-0.92	0.45	-0.05	-0.67	-0.31
2	17	10	11	419	0.13	-0.26	-0.89	-0.36	-0.05	-0.67	1.02
2	17	11	13	389	0.11	-0.35	-0.95	0.02	-0.05	-0.67	0.00
2	17	12	17	392	0.06	-0.26	-0.89	0.05	-0.05	-0.67	0.62
2	17	13	4	362	0.17	0.15	-1.08	0.01	-0.05	-0.67	-0.67
2	17	14	9	424	0.17	0.37	-0.89	-0.29	-0.76	-0.67	0.90
2	17	15	12	395	0.09	-0.06	-1.27	-0.09	-0.05	-0.67	0.37
2	17	16	18	399	0.11	-0.17	-0.89	0.09	-0.05	-0.67	1.05
2	17	17	15	373	0.09	-0.59	-0.89	0.45	-0.05	-0.67	-0.58
2	17	18	11	357	0.09	0.20	-0.89	0.47	-0.05	-0.67	0.68
2	17	19	15	398	0.26	0.98	-0.89	-0.41	-0.57	-0.67	0.49
2	17	20	20	367	0.08	0.25	-0.91	0.05	-0.05	-0.67	0.46
2	17	21	3	438	0.08	-0.60	-0.89	0.04	-0.76	-0.67	0.48
2	17	22	6	429	0.08	-0.22	-0.89	-0.07	-0.76	-0.67	0.68
2	17	23	15	382	0.08	-0.35	-0.92	0.45	-0.05	-0.67	0.47
2	18	1	4	430	0.06	-0.12	2.30	-0.78	-0.76	-0.67	0.52
2	18	2	5	199	0.07	0.53	2.30	0.46	-0.05	0.43	0.62
2	18	3	4	276	0.04	-0.21	2.30	0.03	-0.05	-0.67	-0.48
2	18	4	1	225	0	0.74	2.30	-0.19	-0.05	-0.67	-0.79
2	18	5	4	340	0.08	0.42	2.30	-0.56	-0.76	-0.67	-0.64
2	18	6	16	286	0.15	0.56	2.30	0.00	-0.05	-0.67	1.49
2	18	7	5	242	0.04	0.41	2.30	0.45	-0.05	-0.67	0.35
2	18	8	7	187	0.09	0.61	2.30	0.31	-0.05	0.43	1.57
2	18	9	8	200	0.15	0.62	2.30	0.08	-0.05	0.43	0.04
2	18	10	5	226	0.04	0.41	2.30	0.05	-0.05	0.43	0.69
2	18	11	8	463	0.07	0.24	2.30	-0.78	-0.76	-0.67	1.30
2	18	12	9	522	0.08	-0.14	2.30	-1.19	-1.11	-0.67	1.33
2	18	13	2	115	0.08	1.74	2.30	1.23	-0.05	-0.67	-0.03
2	18	14	6	274	0.18	0.31	2.30	-0.06	-0.05	-0.67	0.15
2	18	15	3	229	0.06	0.55	2.30	-0.06	-0.05	0.43	1.14
2	18	16	10	254	0.13	0.67	2.30	0.22	-0.05	-0.67	0.87
2	18	17	4	407	0.13	0.00	2.30	-0.78	-0.76	0.43	0.94
2	18	18	7	246	0.08	0.16	2.30	-0.04	-0.05	0.43	1.57
2	18	19	4	339	0.04	-0.04	2.30	0.05	-0.76	-0.67	0.04
2	18	20	3	217	0.01	0.65	2.30	0.03	-0.05	0.43	0.69
2	18	21	3	476	0.14	-0.52	2.30	-0.45	-0.76	-0.67	1.29
2	18	22	0	NA	NA	NA	NA	NA	NA	NA	NA
2	18	23	0	NA	NA	NA	NA	NA	NA	NA	NA
2	19	1	6	391	0.18	0.52	-0.89	-0.34	-0.64	0.43	0.98
2	19	2	6	383	0.07	0.68	-0.89	-0.56	-0.76	0.43	0.10
2	19	3	21	470	0.12	-1.02	-0.91	-0.76	-0.76	0.43	0.53
2	19	4	11	348	0.2	0.08	-1.03	-0.10	-0.05	0.43	0.14
2	19	5	10	446	0.15	-1.12	-0.81	-0.30	-0.76	0.43	0.01
2	19	6	14	350	0.08	0.07	-0.89	0.05	-0.05	0.43	0.74
2	19	7	8	388	0.27	-0.53	-0.38	-0.56	-0.40	0.43	-0.28
2	19	8	7	467	0.11	-1.18	-0.89	-0.29	-0.76	0.43	0.88
2	19	9	6	425	0.09	-0.49	-0.89	-0.23	-0.76	0.43	0.58
2	19	10	9	406	0.1	-0.18	-0.08	-0.75	-0.76	0.43	0.63
2	19	11	10	400	0.16	-0.36	-0.89	-0.71	-0.05	0.43	0.33
2	19	12	9	347	0.21	-0.22	-0.89	0.49	-0.13	0.43	0.63
2	19	13	8	497	0.1	-0.83	-0.89	-1.19	-1.11	0.43	0.44
2	19	14	16	378	0.12	-0.25	-1.03	-0.12	-0.05	0.43	0.74
2	19	15	16	418	0.15	-0.73	-0.08	-0.41	-0.76	0.43	0.82
2	19	16	22	448	0.15	-0.21	-0.94	-0.82	-0.76	0.43	0.77
2	19	17	13	485	0.15	-0.74	-0.95	-0.83	-0.76	0.43	1.20
2	19	18	13	447	0.14	-0.52	-0.98	-0.75	-0.76	0.43	0.17
2	19	19	10	412	0.21	-0.48	-0.81	-0.43	-0.05	0.43	1.25
2	19	20	11	355	0.16	-0.61	-0.89	0.20	-0.05	0.43	-0.14
2	19	21	9	390	0.1	-0.66	-0.89	-0.14	-0.05	0.43	0.65
2	19	22	10	401	0.15	-0.52	-0.93	0.13	-0.05	0.43	1.40
2	19	23	11	487	0.12	-0.83	-1.27	-0.86	-0.76	0.43	0.75
2	20	1	5	73	0.02	-0.13	0.68	1.70	1.37	0.43	-2.46
2	20	2	3	69	0.02	-0.02	0.68	2.29	1.37	0.43	-1.98
2	20	3	3	65	0.19	-0.83	1.22	3.07	-0.05	-0.67	-2.46
2	20	4	7	79	0.03	0.82	2.30	1.21	1.37	0.43	-0.92
2	20	5	5	62	0.03	0.13	0.68	2.29	1.37	0.43	-2.32
2	20	6	3	80	0.04	-0.03	0.68	1.70	1.37	0.43	-2.19
2	20	7	3	71	0.03	0.47	2.30	1.70	1.37	0.43	-0.79
2	20	8	2	72	0	0.22	0.68	1.70	1.37	0.43	-2.46
2	20	9	12	35	0.14	0.15	2.30	2.29	1.37	0.43	-2.29
2	20	10	4	44	0.06	-0.03	0.68	3.07	1.37	0.43	-2.25
2	20	11	11	42	0.07	0.15	2.30	1.70	1.37	0.43	-2.39
2	20	12	1	31	0	0.57	2.30	3.30	1.37	0.43	-1.25
2	20	13	5	63	0.08	-0.29	0.68	2.29	1.37	0.43	-2.35
2	20	14	6	66	0.05	0.39	2.30	1.70	1.37	0.43	-1.23
2	20	15	1	68	0	0.31	0.68	2.29	1.37	0.43	-1.98
2	20	16	3	78	0.05	1.06	2.30	1.23	1.37	0.43	-0.62
2	20	17	4	27	0.05	0.19	2.30	3.07	1.37	0.43	-2.25
2	20	18	0	NA	NA	NA	NA	NA	NA	NA	NA
2	20	19	0	NA	NA	NA	NA	NA	NA	NA	NA
2	20	20	0	NA	NA	NA	NA	NA	NA	NA	NA
2	20	21	0	NA	NA	NA	NA	NA	NA	NA	NA
2	20	22	0	NA	NA	NA	NA	NA	NA	NA	NA
2	20	23	0	NA	NA	NA	NA	NA	NA	NA	NA
2	21	1	4	504	0.17	0.72	-0.89	-0.66	-0.76	2.64	1.36
2	21	2	5	245	0.17	0.97	0.68	-0.65	-0.62	2.64	1.03
2	21	3	6	313	0.16	-0.20	0.68	-0.40	-0.52	2.64	0.41
2	21	4	10	338	0.18	0.27	-0.89	-0.34	-0.05	2.64	0.32
2	21	5	4	375	0.13	0.16	-0.49	0.04	-0.76	2.64	0.66
2	21	6	6	298	0.15	1.35	-0.08	-0.45	-0.76	2.64	0.94
2	21	7	10	526	0.21	-0.31	-1.08	-0.88	-0.76	2.64	1.28
2	21	8	11	490	0.15	-0.83	-0.89	-0.25	-0.76	2.64	-0.33
2	21	9	6	393	0.19	1.39	-0.89	-0.56	-0.76	2.64	-0.04
2	21	10	8	359	0.11	0.49	-0.89	-0.39	-0.05	2.64	0.95
2	21	11	6	295	0.1	0.19	-0.08	-0.29	-0.05	2.64	0.75
2	21	12	7	376	0.09	-0.05	-0.89	-0.19	-0.05	2.64	0.77
2	21	13	18	205	0.2	0.58	0.68	-0.13	-0.13	2.64	0.65
2	21	14	6	186	0.18	0.55	0.55	0.01	-0.05	2.64	1.50
2	21	15	6	328	0.14	0.27	-0.89	-0.73	-0.05	2.64	-0.76
2	21	16	2	215	0.1	0.75	-0.08	-0.46	-0.05	2.64	-0.35
2	21	17	5	408	0.12	-0.53	-0.08	-0.29	-0.76	2.64	0.19

Now let’s check the compression summary for HVT (map C). The table below shows no of cells, no of cells having quantization error below threshold and percentage of cells having quantization error below threshold for each level.

mapC_compression_summary <- map_C[[3]]$compression_summary %>%  dplyr::mutate_if(is.numeric, funs(round(.,4)))
compressionSummaryTable(mapC_compression_summary)

segmentLevel	noOfCells	noOfCellsBelowQuantizationError	percentOfCellsBelowQuantizationErrorThreshold	parameters
1	23	0	0	n_cells: 23 quant.err: 0.2 distance_metric: L1_Norm error_metric: max quant_method: kmeans
2	508	434	0.85	n_cells: 23 quant.err: 0.2 distance_metric: L1_Norm error_metric: max quant_method: kmeans

As it can be seen from the table above, 0% of the cells have hit the quantization threshold error in level 1 and 85% of the cells have hit the quantization threshold error in level 2

Let’s plot the Voronoi tessellation for layer 2 (map C)

muHVT::plotHVT(map_C,
        line.width = c(0.4,0.2), 
        color.vec = c("#141B41","#0582CA"),
        centroid.size = 0.1,
        maxDepth = 2)

Figure 14: The Voronoi Tessellation for layer 2 (map C) shown for the 100 cells in the dataset ’computers’ at level 2

Heat Maps

Now let’s plot all the features for each cell at level two as a heatmap for better visualization.


  hvtHmap(
  map_C,
  trainComputers,
  child.level = 2,
  hmap.cols = "n",
  line.width = c(0.6,0.4),
  color.vec = c("#141B41","#0582CA"),
  palette.color = 6,
  centroid.size = 0.1,
  show.points = T,
  quant.error.hmap = 0.2,
  n_cells.hmap = 100,
)

Figure 15: The Voronoi Tessellation with the heat map overlaid for features No. of entities in each cell


  hvtHmap(
  map_C,
  trainComputers,
  child.level = 2,
  hmap.cols = "price",
  line.width = c(0.6,0.4),
  color.vec = c("#141B41","#0582CA"),
  palette.color = 6,
  centroid.size = 0.1,
  show.points = T,
  quant.error.hmap = 0.2,
  n_cells.hmap = 100,
)

Figure 16: The Voronoi Tessellation with the heat map overlaid for features price in the ’computers’ dataset


  hvtHmap(
  map_C,
  trainComputers,
  child.level = 2,
  hmap.cols = "speed",
  line.width = c(0.6,0.4),
  color.vec = c("#141B41","#0582CA"),
  palette.color = 6,
  centroid.size = 0.1,
  show.points = T,
  quant.error.hmap = 0.2,
  n_cells.hmap = 100,
)

Figure 17: The Voronoi Tessellation with the heat map overlaid for features speed in the ’computers’ dataset


  hvtHmap(
  map_C,
  trainComputers,
  child.level = 2,
  hmap.cols = "hd",
  line.width = c(0.6,0.4),
  color.vec = c("#141B41","#0582CA"),
  palette.color = 6,
  centroid.size = 0.1,
  show.points = T,
  quant.error.hmap = 0.2,
  n_cells.hmap = 100,
)

Figure 18: The Voronoi Tessellation with the heat map overlaid for features hd in the ’computers’ dataset


  hvtHmap(
  map_C,
  trainComputers,
  child.level = 2,
  hmap.cols = "ram",
  line.width = c(0.6,0.4),
  color.vec = c("#141B41","#0582CA"),
  palette.color = 6,
  centroid.size = 0.1,
  show.points = T,
  quant.error.hmap = 0.2,
  n_cells.hmap = 100,
)

Figure 19: The Voronoi Tessellation with the heat map overlaid for features ram in the ’computers’ dataset


  hvtHmap(
  map_C,
  trainComputers,
  child.level = 2,
  hmap.cols = "screen",
  line.width = c(0.6,0.4),
  color.vec = c("#141B41","#0582CA"),
  palette.color = 6,
  centroid.size = 0.1,
  show.points = T,
  quant.error.hmap = 0.2,
  n_cells.hmap = 100,
)

Figure 20: The Voronoi Tessellation with the heat map overlaid for features screen in the ’computers’ dataset


  hvtHmap(
  map_C,
  trainComputers,
  child.level = 2,
  hmap.cols = "ads",
  line.width = c(0.6,0.4),
  color.vec = c("#141B41","#0582CA"),
  palette.color = 6,
  centroid.size = 0.1,
  show.points = T,
  quant.error.hmap = 0.2,
  n_cells.hmap = 100,
)

Figure 21: The Voronoi Tessellation with the heat map overlaid for features ads in the ’computers’ dataset

We now have the set of maps (map A, map B & map C) which will be used to predict which map and cell each test record is assigned to, but before that lets view our test dataset

6 Prediction on Test Data

Now once we have built the model, let us try to predict using our test dataset (containing 1252 data points) which cell and which layer each point belongs to.

Raw Testing Dataset

The testing dataset includes the following columns:

Price: The price of 486 PCs in US dollars.
Speed: The clock speed of the PCs in MHz.
HD: The size of the hard drive in MB.
RAM: The size of RAM in MB.
Screen: The size of the screen in inches.
Ads: The number of listings for 486 PCs’ prices for each month.

Let’s have a look at our randomly selected test dataset containing 1252 datapoints.

Table(head(testComputers_data))

Row.No	price	speed	hd	ram	screen	ads
3	1595	25	170	4	15	94
4	1849	25	170	8	14	94
7	1720	25	170	4	14	94
10	2575	50	210	4	15	94
11	2195	33	170	8	15	94
14	2295	25	245	8	14	94

The predictLayerHVT function is used to score the test data using the predictive set of maps. This function takes an input - a test data and a set of maps (map A, map B, map C).

Now, Let us understand the predictLayerHVT function.

predictLayerHVT(data,
                map_A,
                map_B,
                map_C,
                mad.threshold = 0.2,
                normalize = T, 
                distance_metric="L1_Norm",
                error_metric="max",
                child.level = 1, 
                line.width = c(0.6, 0.4, 0.2),
                color.vec = c("#141B41", "#6369D1", "#D8D2E1"),
                yVar= NULL,
                ...)

Each of the parameters of predictLayerHVT function has been explained below:

data - A dataframe containing the test dataset. The variables from this dataset can also be used to overlay as heatmap.
map A - A list of hvt.results.model obtained from HVT function while performing hierarchical vector quantization on train data. This list containes information about the hierarchical vector quantized data along with a summary section.
map B - A list of hvt.results.model obtained from HVT function while performing hierarchical vector quantization on data with novelty which was obtained as a result of removeNovelty function.
map C - A list of hvt.results.model obtained from HVT function while performing hierarchical vector quantization on data without novelty obtained as a result of removeNovelty function.
child.level - A number indicating the layer for which the heat map is to be plotted.(Only used if hmap.cols is not NULL).It specifies the specific layer within the hierarchical structure of the model.
mad.threshold - A threshold value used to filter data based on the Median Absolute Deviation (MAD) of the Quant.Error variable. It determines how extreme a deviation from the median has to be in order to be considered an novelty
normalize - A logical value indicating if the columns in the dataset should be normalized. If set to TRUE, the algorithm will normalize the data before performing compression. The default value is TRUE
distance_metric - It specifies the type of distance measurement used to calculate similarity or dissimilarity between data points.The distance calculation involves taking the difference between centroid_data and data_vec either by using Euclidean which calculates the sum of squared differences for each column and takes the square root or Manhattan which calculates the sum of absolute differences for each column. Euclidean is selected by default.
error_metric - It specifies the error metrics to be used for evaluating the performance of the model. It can be “mean” or “max”. If error_metric is set to mean, the code calculates the mean quantization error within each group while if the error_metric is not set to max, the code calculates the maximum quantization error within each group of columns. mean is selected by default.
yVar - Name of the dependent variable(s).
... - color.vec and line.width can be passed from here.

The function predicts based on the HVT maps - map A, map B and map C, constructed using HVT function. For each test record, the function will assign that record to Layer1 or Layer2. Layer1 contains the cell ids from map A and Layer 2 contains cell ids from map B (novelty map) and map C (map without novelty).

Prediction Algorithm

The prediction algorithm recursively calculates the distance between each point in the test dataset and the cell centroids for each level. The following steps explain the prediction method for a single point in the test dataset:

Calculate the distance between the point and the centroid of all the cells in the first level.
Find the cell whose centroid has minimum distance to the point.
Check if the cell drills down further to form more cells.
If it doesn’t, return the path. Or else repeat steps 1 to 4 till we reach a level at which the cell doesn’t drill down further.

Note : The prediction algorithm will not work if some of the variables used to perform quantization are missing. In the test dataset, we should not remove any features


validation_data <- testComputers
new_predict <- predictLayerHVT(
    data=validation_data,
    map_A,
    map_B,
    map_C,
    normalize = T
  )

summary_list <- map_A[[3]]

train_colnames <- names(summary_list[["nodes.clust"]][[1]][[1]])
scaled_test_data <- scale(
     testComputers[, train_colnames],
      center = summary_list$scale_summary$mean_data[train_colnames],
      scale = summary_list$scale_summary$std_data[train_colnames]) %>% data.frame()
      scaled_test_data$Row.No <- row.names(testComputers)

predictions <- new_predict %>%
  dplyr::select(Layer1.Cell.ID, Layer2.Cell.ID) %>%
  mutate(Cell.ID = as.numeric(gsub("[A]", "", Layer1.Cell.ID)),
  Row.No = row.names(testComputers))

merged_df <- merge(predictions,scaled_test_data, by = "Row.No", all.x = TRUE) %>%
             arrange(as.numeric(Row.No)) %>% select(Row.No, price, speed, hd, ram, screen, ads, Layer1.Cell.ID, Layer2.Cell.ID) 
  
colnames(merged_df) <- c("Row.No", "price_act", "speed_act", "hd_act", "ram_act", "screen_act", "ads_act",
                         "Layer1.Cell.ID", "Layer2.Cell.ID")


combined <- merged_df %>%
  mutate(Cell.ID = gsub("[C]", "", Layer2.Cell.ID)) %>%
  merge(map_C[[3]]$summary, by = "Cell.ID", all.x = TRUE) %>%
  arrange(as.numeric(Row.No)) %>%
  select(Row.No, price_act, speed_act, hd_act, ram_act, screen_act, ads_act, Layer1.Cell.ID, Layer2.Cell.ID,
  Segment.Level, Segment.Parent, Segment.Child, n, Quant.Error, price, speed, hd, ram, screen, ads)


merged_df <- combined %>%
             mutate(Cell.ID = gsub("[B]", "", Layer2.Cell.ID)) %>%
             merge(map_B[[3]]$summary, by = "Cell.ID", all.x = TRUE) %>%
             arrange(as.numeric(Row.No)) %>%
             select(Row.No, price_act, speed_act, hd_act, ram_act, screen_act, ads_act, Layer1.Cell.ID, Layer2.Cell.ID,
             price.x, speed.x, hd.x, ram.x, screen.x, ads.x, price.y, speed.y, hd.y, ram.y, screen.y, ads.y)%>%
             mutate(price_pred = coalesce(price.x, price.y),
             speed_pred = coalesce(speed.x, speed.y),
             hd_pred = coalesce(hd.x, hd.y),
             ram_pred = coalesce(ram.x, ram.y),
             screen_pred = coalesce(screen.x, screen.y),
             ads_pred = coalesce(ads.x, ads.y)) %>%
             select(Row.No, price_act, speed_act, hd_act, ram_act, screen_act, ads_act, Layer1.Cell.ID, Layer2.Cell.ID,
             price_pred, speed_pred, hd_pred, ram_pred, screen_pred, ads_pred)

Let’s see which cell and layer each point belongs to and check the Mean Absolute Difference for each of the 1252 records.

sorted_df <- merged_df
sorted_df$diff <- rowMeans(abs(sorted_df[, c("price_act","speed_act","hd_act","ram_act","screen_act","ads_act")] - sorted_df[, c("price_pred","speed_pred","hd_pred","ram_pred","screen_pred","ads_pred")]))
rownames(sorted_df) <- NULL
options(scipen = 999)
sorted_df %>% head(1000) %>%as.data.frame() %>%Table(scroll = T)

Row.No	price_act	speed_act	hd_act	ram_act	screen_act	ads_act	Layer1.Cell.ID	Layer2.Cell.ID	price_pred	speed_pred	hd_pred	ram_pred	screen_pred	ads_pred	diff
3	-1.0785679	-1.2710382	-0.9472574	-0.7589986	0.4307274	-1.7213059	A24	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.4690860
4	-0.6386691	-1.2710382	-0.9472574	-0.0501185	-0.6741149	-1.7213059	A143	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.4423148
7	-0.8620823	-1.2710382	-0.9472574	-0.7589986	-0.6741149	-1.7213059	A29	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.3712467
10	0.6186793	-0.0817113	-0.7914378	-0.7589986	0.4307274	-1.7213059	A237	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.3987279
11	-0.0394370	-0.8904536	-0.9472574	-0.0501185	0.4307274	-1.7213059	A223	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.3772636
14	0.1337515	-1.2710382	-0.6550957	-0.0501185	-0.6741149	-1.7213059	A162	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.3302613
15	0.8334330	-0.0817113	-0.7836469	-0.0501185	-0.6741149	-1.7213059	A215	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.3328827
19	-0.2126255	-0.8904536	-0.6356183	-0.7589986	0.4307274	-1.7213059	A165	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.4049168
22	0.9996940	0.6794579	-1.1030770	-0.7589986	-0.6741149	-1.7213059	A214	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.5427801
24	1.1382448	-0.0817113	-0.7914378	-0.7589986	2.6404120	-1.7213059	A379	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.7270993
28	3.0779559	-0.8904536	0.1512706	-0.0501185	-0.6741149	-1.7213059	A367	C201	1.5745305	0.4514353	-0.2367672	0.2737663	-0.3026593	-1.3041998	0.7242998
29	1.5192595	-0.8904536	-0.2850242	1.3676416	-0.6741149	-1.7213059	A316	C201	1.5745305	0.4514353	-0.2367672	0.2737663	-0.3026593	-1.3041998	0.5546423
33	0.6533170	-0.8904536	-0.7914378	-0.0501185	2.6404120	-1.7213059	A343	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.6569287
39	0.3242589	-0.0817113	-0.7914378	-0.0501185	-0.6741149	-1.7213059	A215	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.2493188
40	0.3588966	-0.0817113	-0.7914378	-0.0501185	-0.6741149	-1.7213059	A215	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.2550918
43	0.4870561	-0.8904536	-0.7836469	-0.0501185	-0.6741149	-1.7213059	A187	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.3049914
46	0.8265055	-0.8904536	-0.6550957	-0.0501185	-0.6741149	-1.7213059	A187	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.3822895
48	-0.8118576	-1.2710382	-1.1420319	-0.7589986	-0.6741149	-1.7213059	A29	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.4120799
53	1.3460710	0.6794579	-0.2850242	-0.0501185	0.4307274	-1.7213059	A330	C201	1.5745305	0.4514353	-0.2367672	0.2737663	-0.3026593	-1.3041998	0.3298528
62	-0.7321909	-0.8904536	-0.9472574	-0.7589986	0.4307274	-1.7213059	A24	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.4633848
73	-0.9053794	-0.8904536	-0.9472574	-0.7589986	-0.6741149	-1.7213059	A43	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.3005997
74	1.4309333	-0.0817113	-0.6550957	-0.0501185	-0.6741149	-1.7213059	A215	C201	1.5745305	0.4514353	-0.2367672	0.2737663	-0.3026593	-1.3041998	0.3679198
80	-1.0196838	-1.2710382	-1.2978514	-0.0501185	-0.6741149	-1.7213059	A10	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.5204847
85	0.6533170	-1.2710382	-0.6550957	-0.0501185	-0.6741149	-1.7213059	A187	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.4168555
86	-0.3788864	-0.8904536	-1.1420319	-0.0501185	-0.6741149	-1.7213059	A143	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.3680494
93	0.3502371	-0.8904536	-0.9472574	-0.0501185	0.4307274	-1.7213059	A223	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.4077083
99	0.6533170	-1.2710382	-0.2850242	1.3676416	-0.6741149	-1.7078621	A316	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.6314472
100	-0.9053794	-0.8904536	-0.9472574	-0.7589986	-0.6741149	-1.7078621	A43	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.2983591
104	1.3529985	0.6794579	-0.3239791	-0.7589986	0.4307274	-1.7078621	A330	C201	1.5745305	0.4514353	-0.2367672	0.2737663	-0.3026593	-1.3041998	0.4510968
106	1.3460710	0.6794579	-0.6356183	-0.0501185	2.6404120	-1.7078621	A386	C142	0.1328959	0.6627507	0.4814828	-0.0248014	2.6404120	-0.9712527	0.5181517
110	-0.1260312	0.6794579	-0.9472574	-0.7589986	-0.6741149	-1.7078621	A166	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.3903145
111	1.3460710	0.6794579	-0.2850242	-0.0501185	0.4307274	-1.7078621	A330	C201	1.5745305	0.4514353	-0.2367672	0.2737663	-0.3026593	-1.3041998	0.3276122
115	-1.2448289	-1.2710382	-0.9472574	-0.7589986	-0.6741149	-1.7078621	A10	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.3258541
118	0.1857081	0.6794579	-0.6356183	-0.0501185	-0.6741149	-1.7078621	A250	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.3735189
133	0.0038602	-0.8904536	-0.6356183	-0.7589986	-0.6741149	-1.7078621	A121	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.2683436
157	1.3529985	-0.0817113	-0.9472574	-0.7589986	-0.6741149	-1.7078621	A214	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.4465921
158	-0.0394370	-0.8904536	-0.9472574	-0.0501185	0.4307274	-1.7078621	A223	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.3750230
160	2.0457525	0.6794579	-0.7135281	-0.7589986	0.4307274	-1.7078621	A330	C201	1.5745305	0.4514353	-0.2367672	0.2737663	-0.3026593	-1.3041998	0.5576366
168	0.6602445	-0.0817113	-0.7914378	-0.7589986	-0.6741149	-1.7078621	A214	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.3051632
174	0.9113679	0.6794579	-0.6550957	-0.0501185	-0.6741149	-1.7078621	A250	C201	1.5745305	0.4514353	-0.2367672	0.2737663	-0.3026593	-1.3041998	0.4014194
175	2.7315789	-0.8904536	0.1512706	-0.0501185	-0.6741149	-1.7078621	A367	C201	1.5745305	0.4514353	-0.2367672	0.2737663	-0.3026593	-1.3041998	0.6643296
176	0.9130997	0.6794579	-0.6356183	-0.7589986	0.4307274	-1.7078621	A292	C201	1.5745305	0.4514353	-0.2367672	0.2737663	-0.3026593	-1.3041998	0.5763531
177	0.3138676	-0.0817113	-0.7836469	-0.7589986	-0.6741149	-1.7078621	A126	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.2461352
184	0.7381794	-0.0817113	-0.6550957	-0.0501185	-0.6741149	-1.7078621	A215	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.3354896
188	0.6186793	0.6794579	-0.6356183	-0.0501185	-0.6741149	-1.7078621	A250	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.4456807
189	0.8265055	-0.8904536	-0.2850242	1.3676416	-0.6741149	-1.7078621	A316	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.5391517
190	1.3529985	0.6794579	-0.6550957	1.3676416	0.4307274	-1.6406430	A370	C201	1.5745305	0.4514353	-0.2367672	0.2737663	-0.3026593	-1.3041998	0.5052647
202	0.9823751	-0.8904536	-0.6356183	-0.0501185	2.6404120	-1.6406430	A343	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.6723580
205	-1.0785679	-0.8904536	-1.2783740	-1.1134387	-0.6741149	-1.6406430	A6	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.3725506
208	2.7315789	-0.8904536	0.1512706	-0.0501185	-0.6741149	-1.6406430	A367	C201	1.5745305	0.4514353	-0.2367672	0.2737663	-0.3026593	-1.3041998	0.6531265
210	2.9047674	0.6794579	0.3382540	-0.0501185	0.4307274	-1.6406430	A382	C201	1.5745305	0.4514353	-0.2367672	0.2737663	-0.3026593	-1.3041998	0.5878326
221	0.7225924	-0.8904536	-0.6356183	-0.0501185	2.6404120	-1.6406430	A343	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.6290609
225	0.6602445	-0.0817113	-0.7836469	-0.0501185	-0.6741149	-1.6406430	A215	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.2905741
226	0.9130997	0.6794579	-0.9472574	-0.0501185	-0.6741149	-1.6406430	A250	C201	1.5745305	0.4514353	-0.2367672	0.2737663	-0.3026593	-1.3041998	0.4386212
228	1.1728825	-0.0817113	-0.2850242	1.3676416	-0.6741149	-1.6406430	A366	C201	1.5745305	0.4514353	-0.2367672	0.2737663	-0.3026593	-1.3041998	0.4641376
233	-0.3788864	-0.8904536	-0.9472574	-0.7589986	-0.6741149	-1.6406430	A85	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.3242305
235	-0.0394370	-1.2710382	-0.6550957	-0.0501185	-0.6741149	-1.6406430	A162	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.3224537
237	-1.0785679	-1.2710382	-0.9472574	-0.7589986	0.4307274	-1.6406430	A24	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.4556422
245	0.6186793	0.6794579	-0.6356183	-0.0501185	-0.6741149	-1.6406430	A250	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.4344775
247	1.8725640	0.6794579	-0.6550957	1.3676416	0.4307274	-1.6406430	A370	C201	1.5745305	0.4514353	-0.2367672	0.2737663	-0.3026593	-1.3041998	0.5180150
248	0.8334330	0.6794579	-0.7797514	-0.0501185	-0.6741149	-1.6406430	A250	C201	1.5745305	0.4514353	-0.2367672	0.2737663	-0.3026593	-1.3041998	0.4239813
254	-0.8620823	-1.2710382	-0.9472574	-0.7589986	-0.6741149	-1.6406430	A29	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.3578029
282	-0.3858139	-0.8904536	-0.6356183	-0.7589986	-0.6741149	-1.6406430	A85	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.3220861
283	0.1406791	-0.0817113	-0.7836469	-0.7589986	-0.6741149	-1.6406430	A126	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.2060673
285	0.5667228	0.6794579	-0.6356183	-0.0501185	0.4307274	-1.6406430	A292	C201	1.5745305	0.4514353	-0.2367672	0.2737663	-0.3026593	-1.3041998	0.5047327
308	0.1164327	-0.0817113	-0.6356183	-0.0501185	-0.6741149	-1.5330924	A215	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.2059831
310	2.7315789	-0.8904536	0.1512706	-0.0501185	-0.6741149	-1.5330924	A367	C201	1.5745305	0.4514353	-0.2367672	0.2737663	-0.3026593	-1.3041998	0.6352014
312	0.6602445	-0.0817113	-0.7836469	-0.0501185	-0.6741149	-1.5330924	A215	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.2726490
313	1.1728825	-0.0817113	-0.2850242	1.3676416	-0.6741149	-1.5330924	A366	C201	1.5745305	0.4514353	-0.2367672	0.2737663	-0.3026593	-1.3041998	0.4462125
320	-0.0394370	0.6794579	-0.9472574	-0.7589986	-0.6741149	-1.5330924	A166	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.3467538
325	-0.9140388	-0.8904536	-1.2783740	-1.1134387	-0.6741149	-1.5330924	A6	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.3820470
329	1.5106000	0.6794579	-0.2850242	1.3676416	-0.6741149	-1.5330924	A366	C201	1.5745305	0.4514353	-0.2367672	0.2737663	-0.3026593	-1.3041998	0.3390723
330	0.6602445	-0.8904536	-0.6745732	-0.7589986	0.4307274	-1.5330924	A165	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.4203032
332	-0.0394370	-0.0817113	-1.1030770	-0.7589986	-0.6741149	-1.5330924	A126	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.2458622
348	0.6533170	-0.0817113	-0.6356183	-0.0501185	0.4307274	-1.5330924	A261	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.3937154
349	0.5147662	-0.8904536	-0.6356183	-0.0501185	0.4307274	-1.5330924	A223	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.4004619
355	-0.2472631	0.6794579	-0.9472574	-0.7589986	-0.6741149	-1.5330924	A166	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.3813915
356	1.0066215	-0.0817113	-0.6745732	-0.7589986	0.4307274	-1.5330924	A237	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.4481944
360	0.1337515	-0.8904536	-0.6550957	-0.0501185	-0.6741149	-1.5330924	A162	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.2354616
380	-1.2604158	-1.2710382	-1.2783740	-1.1134387	-0.6741149	-1.5330924	A6	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.4135831
389	-1.4249449	-1.2710382	-1.2783740	-1.1134387	-0.6741149	-1.5330924	A6	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.4410046
397	0.4004618	-0.8904536	-0.7135281	-0.7589986	-0.6741149	-1.5330924	A121	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.2722620
399	-0.5520749	-0.8904536	-0.7836469	-0.7589986	-0.6741149	-1.1163339	A104	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.2313867
405	1.1642231	-0.8904536	0.1512706	1.3676416	-0.6741149	-1.1163339	A301	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.4148139
406	-0.0480964	-0.8904536	-0.7758559	-0.7589986	0.4307274	-1.1163339	A165	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.3532435
417	-0.3858139	-0.8904536	-0.6356183	-0.0501185	-0.6741149	-1.1163339	A142	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.3325637
424	0.4801285	-0.0817113	-0.6356183	-0.0501185	0.4307274	-1.1163339	A261	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.3953408
425	0.3242589	-0.0817113	-0.6356183	-0.0501185	-0.6741149	-1.1163339	A215	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.2711109
430	0.1337515	-1.2710382	-0.2850242	-0.0501185	-0.6741149	-1.1163339	A201	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.3910610
437	1.0170128	-0.8904536	-0.6356183	-0.0501185	2.6404120	-1.1163339	A343	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.5907461
446	0.6602445	-0.8904536	-0.6550957	1.3676416	0.4307274	-1.1163339	A345	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.6451381
452	0.3069400	-0.8904536	-0.6356183	-0.0501185	-0.6741149	-1.1163339	A187	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.2980627
454	0.3588966	0.6794579	-0.6356183	-0.0501185	0.4307274	-1.1163339	A292	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.4502568
455	0.5147662	-0.8904536	-0.6356183	-0.0501185	0.4307274	-1.1163339	A226	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.4309520
463	2.2120134	0.6794579	0.3382540	-0.0501185	-0.6741149	-1.1163339	A337	C201	1.5745305	0.4514353	-0.2367672	0.2737663	-0.3026593	-1.3041998	0.3872889
477	-0.3165385	-0.8904536	-0.6356183	-0.0501185	-0.6741149	-1.1163339	A142	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.3210178
488	0.6602445	-0.0817113	-0.0318174	-0.7589986	0.4307274	-1.1163339	A237	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.5280810
493	-0.0394370	-0.0817113	-0.7758559	-0.7589986	-0.6741149	-1.1163339	A152	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.2237104
495	0.8178461	-0.0817113	-0.2850242	-0.0501185	0.4307274	-1.1163339	A261	C201	1.5745305	0.4514353	-0.2367672	0.2737663	-0.3026593	-1.3041998	0.4305376
497	1.3374115	-0.0817113	0.1512706	1.3676416	0.4307274	-1.1163339	A370	C201	1.5745305	0.4514353	-0.2367672	0.2737663	-0.3026593	-1.3041998	0.5289052
499	-0.0480964	-0.8904536	-0.7758559	-0.7589986	-0.6741149	-1.1163339	A104	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.2549919
501	-0.1260312	-0.0817113	-0.9472574	-0.7589986	-0.6741149	-1.1163339	A152	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.2648147
509	0.8178461	-0.0817113	-0.2850242	-0.0501185	-0.6741149	-1.1163339	A228	C201	1.5745305	0.4514353	-0.2367672	0.2737663	-0.3026593	-1.3041998	0.3702157
510	1.6924480	0.6794579	0.4940736	-0.0501185	0.4307274	-1.1163339	A330	C201	1.5745305	0.4514353	-0.2367672	0.2737663	-0.3026593	-1.3041998	0.3869864
512	0.7399113	-0.0817113	-0.6356183	-0.0501185	0.4307274	-1.1163339	A261	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.4386379
515	-0.3788864	-0.8904536	-0.9472574	-0.7589986	-0.6741149	-1.1163339	A104	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.2875199
516	1.2421579	-0.0817113	-0.6356183	-0.0501185	2.6404120	-1.1163339	A379	C142	0.1328959	0.6627507	0.4814828	-0.0248014	2.6404120	-0.9712527	0.5235372
530	0.6186793	-0.0817113	-0.6356183	-0.0501185	0.4307274	-1.1163339	A261	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.4184326
538	-0.5520749	-0.8904536	-0.9472574	-0.7589986	-0.6741149	-0.6189125	A107	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.2009689
540	-0.2126255	-0.8904536	-0.6356183	-0.7589986	-0.6741149	-0.6189125	A107	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.2270607
554	-0.5676619	0.6794579	-1.1926732	-1.1134387	0.4307274	-0.6189125	A164	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.5411040
556	-1.2604158	-0.8904536	-1.1926732	-1.1134387	-0.6741149	-0.6189125	A33	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.2087229
557	-0.2472631	-0.0817113	-0.6356183	-0.0501185	-0.6741149	-0.6189125	A193	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.3625372
565	0.1337515	-0.0817113	-0.7836469	-0.0501185	0.4307274	-0.6189125	A261	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.3965454
566	-0.0480964	-0.8904536	-0.7758559	-0.7589986	-0.6741149	-0.6189125	A107	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.2563984
571	-0.8620823	-0.8904536	-0.9472574	-0.7589986	-0.6741149	-0.6189125	A93	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.1493010
580	-0.2056979	-0.8904536	-1.1420319	-0.7589986	-0.6741149	-0.6189125	A107	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.2911609
585	1.8136799	-0.8904536	0.4940736	-0.0501185	2.6404120	-0.6189125	A391	C142	0.1328959	0.6627507	0.4814828	-0.0248014	2.6404120	-0.9712527	0.6040394
591	0.0471573	-0.8904536	-0.6356183	-0.0501185	0.4307274	-0.6189125	A226	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.4054435
593	1.1642231	-0.8904536	0.1512706	1.3676416	0.4307274	-0.6189125	A340	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.4470960
595	0.1337515	0.6794579	-0.7758559	-0.7589986	-0.6741149	-0.6189125	A178	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.4101111
596	-1.2084593	-1.2710382	-1.2978514	-0.7589986	-0.6741149	-0.6189125	A28	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.2219506
597	0.9130997	-0.8904536	0.4940736	-0.0501185	-0.6741149	-0.6189125	A217	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.4510996
619	0.1250921	-0.0817113	-0.7758559	-0.7589986	0.4307274	-0.6189125	A164	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.3977861
622	-0.3338574	0.6794579	-0.9472574	-0.7589986	-0.6741149	-0.6189125	A150	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.3383311
628	0.3069400	0.6794579	-0.6356183	-0.7589986	-0.6741149	-0.6189125	A178	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.4545456
629	-0.5520749	-0.8904536	-0.6356183	-0.7589986	-0.6741149	-0.6189125	A107	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.1704858
635	-0.5538068	-0.8904536	-1.1030770	-0.7589986	-0.6741149	-0.6189125	A107	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.2266502
644	1.3374115	-0.0817113	0.1512706	1.3676416	0.4307274	-0.6189125	A347	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.5091823
645	-0.5070459	-0.0817113	-0.9472574	-0.7589986	0.4307274	-0.6189125	A164	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.4444599
650	-1.0785679	-0.8904536	-0.9472574	-0.7589986	0.4307274	-0.6189125	A86	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.2471404
657	0.9650563	-0.0817113	-0.6356183	-0.0501185	2.6404120	-0.6189125	A379	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.4906051
662	0.1250921	-0.0817113	-0.7758559	-0.7589986	-0.6741149	-0.6189125	A152	C404	0.0640661	-0.3965677	-0.7815408	-0.3982964	-0.4164485	-1.4161834	0.2995345
679	0.6602445	-0.0817113	0.1434796	-0.0501185	-0.6741149	-0.6189125	A248	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.4054230
681	0.4108531	-0.8904536	-0.6356183	-0.0501185	2.6404120	-0.6189125	A284	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.4068159
685	-0.7321909	0.6794579	-1.1926732	-1.1134387	-0.6741149	-0.6189125	A150	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.4209170
687	2.3332454	0.6794579	0.4940736	-0.0501185	2.6404120	-0.6189125	A391	C142	0.1328959	0.6627507	0.4814828	-0.0248014	2.6404120	-0.9712527	0.4345508
692	0.2203458	-0.0817113	-0.6356183	-0.0501185	0.4307274	-0.6189125	A263	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.4213515
695	-1.4336043	-1.2710382	-1.1926732	-1.1134387	-0.6741149	-0.6189125	A28	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.3010184
698	-1.1062781	-1.2710382	-1.1420319	-0.7589986	-0.6741149	-0.6189125	A28	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.2044949
702	-0.2056979	-0.8904536	-1.1420319	-0.7589986	-0.6741149	-0.6189125	A107	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.2911609
704	1.5106000	0.6794579	0.1512706	1.3676416	0.4307274	-0.6189125	A370	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.4111855
709	-0.7321909	-1.2710382	-0.7758559	-0.7589986	-0.6741149	-0.6189125	A107	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.2058135
717	1.3529985	0.6794579	-0.2655468	1.3676416	0.4307274	0.3624865	A355	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.2908216
722	-0.5676619	-1.2710382	-0.7758559	-0.7589986	0.4307274	0.3624865	A119	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.2319777
725	-0.0325094	0.6794579	-0.2850242	-0.7589986	-0.6741149	0.3624865	A180	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.2891217
726	-0.2212849	0.6794579	-1.1926732	-1.1134387	-0.6741149	0.3624865	A140	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.2649954
728	0.9113679	-0.8904536	0.1512706	1.3676416	-0.6741149	0.3624865	A291	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.1262013
731	-0.5520749	-0.8904536	-0.7135281	-0.7589986	-0.6741149	0.3624865	A92	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.0803848
734	-0.5867126	-0.0817113	-0.7914378	-0.7589986	0.4307274	0.3624865	A149	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.2907739
736	-0.5676619	-0.8904536	-1.1926732	-1.1134387	-0.6741149	0.3624865	A64	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1709408
737	-0.8620823	-0.8904536	-0.7836469	-0.7589986	-0.6741149	0.3624865	A92	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1203663
749	-0.9140388	-0.8904536	-1.1926732	-1.1134387	-0.6741149	0.3624865	A45	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.2286703
751	-0.8118576	-0.8904536	-0.9472574	-0.7589986	-0.6741149	0.3624865	A92	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1116641
762	-1.0872273	-1.2710382	-1.1926732	-1.1134387	-0.6741149	0.3624865	A27	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.2591844
766	-0.1277631	-0.0817113	-1.1926732	-1.1134387	-0.6741149	0.3624865	A91	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.3128929
770	1.0066215	0.6794579	0.1434796	-0.0501185	0.4307274	0.3624865	A297	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.2650227
775	0.8334330	-0.8904536	-0.2655468	1.3676416	0.4307274	0.3624865	A322	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.3048784
784	0.7381794	-0.8904536	-0.2850242	-0.0501185	-0.6741149	0.3624865	A175	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.2403967
801	1.0066215	-0.8904536	-0.6745732	-0.7589986	-0.6741149	0.3624865	A163	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.3336032
806	0.3138676	-0.0817113	-0.2850242	-0.0501185	-0.6741149	0.3624865	A221	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.2137875
824	0.3069400	-0.0817113	-0.2850242	-0.0501185	0.4307274	0.3624865	A238	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.2052761
826	-0.7321909	-0.8904536	-1.1926732	-1.1134387	-0.6741149	0.3624865	A45	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1983623
833	-0.2126255	-0.8904536	-0.7758559	-0.7589986	-0.6741149	0.3624865	A109	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1135150
848	0.0125196	0.6794579	-0.6356183	-0.7589986	-0.6741149	0.3624865	A180	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.2497122
857	-0.7321909	-1.2710382	-0.7758559	-0.7589986	-0.6741149	0.3624865	A87	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1359666
865	2.6016875	0.6794579	0.3382540	-0.0501185	-0.6741149	0.3624865	A300	C219	1.9755430	0.5864499	0.2031375	-0.2014525	0.1203785	0.5809108	0.3364201
868	0.6533170	0.6794579	-0.2850242	-0.0501185	-0.6741149	0.3624865	A253	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.1899706
869	0.6966141	-0.0817113	-0.2850242	-0.0501185	0.4307274	0.3624865	A252	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.2702218
876	0.3918024	-0.8904536	-0.2850242	-0.0501185	-0.6741149	0.3624865	A175	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.1826672
888	1.5106000	0.6794579	0.1512706	1.3676416	-0.6741149	0.3624865	A354	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.2855043
889	-0.2143573	-0.8904536	-0.7758559	-0.7589986	-0.6741149	0.3624865	A109	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1132263
895	0.7918678	0.6794579	-0.2850242	-0.0501185	2.6404120	0.3624865	A357	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.3964077
902	1.3529985	0.6794579	-0.3629340	-0.0501185	0.4307274	0.3624865	A280	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.3240230
911	1.3460710	0.6794579	0.1512706	1.3676416	-0.6741149	0.3624865	A354	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.2580828
921	0.8178461	0.6794579	-0.2850242	-0.0501185	-0.6741149	0.3624865	A253	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.2173921
937	0.9113679	0.6794579	-0.2850242	-0.0501185	-0.6741149	0.3624865	A251	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.2329790
939	-0.3875458	-1.2710382	-0.7758559	-0.7589986	-0.6741149	0.3624865	A87	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1203119
940	-1.2517564	-0.8904536	-0.7836469	-0.7589986	-0.6741149	0.3624865	A65	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1570941
941	-0.2992197	-0.8904536	-0.6356183	-0.0501185	0.4307274	0.3624865	A167	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.1841475
944	-0.0411688	0.6794579	-1.1926732	-1.1134387	-0.6741149	0.3624865	A140	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.2950147
945	2.4094483	0.6794579	0.4434322	-0.7589986	0.4307274	0.3624865	A360	C219	1.9755430	0.5864499	0.2031375	-0.2014525	0.1203785	0.5809108	0.3089213
947	-0.8187852	-0.8904536	-0.7914378	-0.7589986	-0.6741149	0.3624865	A92	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1118516
952	2.3852019	0.6794579	0.3382540	-0.0501185	0.4307274	0.3624865	A360	C219	1.9755430	0.5864499	0.2031375	-0.2014525	0.1203785	0.5809108	0.2196485
955	1.6041218	-0.0817113	0.1512706	1.3676416	-0.6741149	0.3624865	A326	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.3539800
962	-1.2517564	-0.8904536	-0.7836469	-0.7589986	-0.6741149	1.0212337	A53	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1014105
965	0.2186139	-0.8904536	0.0499878	-0.0501185	-0.6741149	1.0212337	A168	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.1496275
966	0.9979621	-0.8904536	0.4940736	1.3676416	-0.6741149	1.0212337	A288	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.1655488
973	2.2189410	0.6794579	0.1434796	-0.0501185	2.6404120	1.0212337	A385	C96	2.0782294	0.7478725	0.1122044	0.7127714	2.6404120	0.5611990	0.2438877
975	0.8265055	0.6794579	-0.2850242	-0.7589986	-0.6741149	1.0212337	A195	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.2961914
977	-0.9053794	-1.2710382	-0.7758559	-0.7589986	-0.6741149	1.0212337	A56	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1741061
991	-0.7321909	-0.0817113	-1.1926732	-1.1134387	-0.6741149	1.0212337	A50	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.2995067
992	-1.0716404	-0.0817113	-0.9472574	-0.7589986	-0.6741149	1.0212337	A51	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.2514187
994	3.9421665	-0.8904536	2.6755476	1.3676416	-0.6741149	1.0212337	A423	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	1.0198285
996	0.3918024	-0.8904536	0.0499878	-0.0501185	-0.6741149	1.0212337	A189	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.1784923
1008	0.6429257	0.6794579	-0.2850242	-0.0501185	2.6404120	1.0212337	A336	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.4039357
1011	0.4783966	-0.0817113	-1.1926732	-0.7589986	-0.6741149	1.0212337	A128	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.3931991
1012	-0.6109590	-1.2710382	-0.9472574	-0.7589986	2.6404120	1.0212337	A1	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.5007895
1013	-0.0740747	0.6794579	-0.6356183	-0.0501185	0.4307274	1.0212337	A247	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.2503772
1018	-0.7408504	-0.8904536	-1.1926732	-1.1134387	0.4307274	1.0212337	A15	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.3560106
1020	-0.9053794	-0.8904536	-0.6356183	-0.7589986	-0.6741149	1.0212337	A72	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1838114
1036	1.0862882	0.6794579	-0.2850242	-0.0501185	2.6404120	1.0212337	A357	C96	2.0782294	0.7478725	0.1122044	0.7127714	2.6404120	0.5611990	0.4467515
1038	1.3529985	0.6794579	0.4940736	-0.0501185	0.4307274	1.0212337	A297	C219	1.9755430	0.5864499	0.2031375	-0.2014525	0.1203785	0.5809108	0.3180824
1039	2.2120134	-0.0817113	0.1512706	-0.0501185	-0.6741149	1.0212337	A257	C219	1.9755430	0.5864499	0.2031375	-0.2014525	0.1203785	0.5809108	0.3904415
1051	0.6446576	-1.2710382	0.4940736	1.3676416	-0.6741149	1.0212337	A290	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.2400317
1052	0.1337515	0.6794579	-0.6356183	-0.0501185	0.4307274	1.0212337	A247	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.2157395
1067	-1.2604158	-1.2710382	-1.1926732	-1.1134387	0.4307274	1.0212337	A15	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.3324035
1076	1.3443391	-0.8904536	0.4940736	1.3676416	-0.6741149	1.0212337	A299	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.2232783
1090	-2.0241771	-0.8904536	-1.2978514	-1.1134387	-0.6741149	1.0212337	A5	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.3023442
1097	0.6533170	-0.8904536	0.4940736	1.3676416	-0.6741149	1.0212337	A288	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.1751576
1112	-0.5607343	-0.8904536	-1.1926732	-1.1134387	-0.6741149	1.0212337	A48	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.2117200
1115	0.1406791	0.6794579	-1.1420319	-0.7589986	-0.6741149	1.0212337	A155	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.2961620
1125	-1.2517564	-0.8904536	-1.1926732	-1.1134387	-0.6741149	1.0212337	A32	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1624117
1130	0.8247736	-1.2710382	0.4940736	1.3676416	-0.6741149	1.0212337	A290	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.2100123
1138	-1.2448289	-0.8904536	-1.1030770	-0.7589986	-0.6741149	1.0212337	A47	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1137335
1141	-0.3858139	-1.2710382	0.0499878	-0.0501185	-0.6741149	1.0212337	A159	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.2066937
1145	3.0848834	0.6794579	0.1434796	-0.0501185	2.6404120	1.0212337	A394	C96	2.0782294	0.7478725	0.1122044	0.7127714	2.6404120	0.5611990	0.3882114
1155	3.2511444	0.6794579	0.3382540	1.3676416	2.6404120	1.0212337	A413	C96	2.0782294	0.7478725	0.1122044	0.7127714	2.6404120	0.5611990	0.4303807
1160	-1.0716404	0.6794579	-1.1030770	-0.7589986	-0.6741149	1.0212337	A67	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.2782722
1172	1.3374115	-0.0817113	0.4940736	1.3676416	-0.6741149	1.0212337	A333	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.3344434
1174	-0.3511762	0.6794579	-0.7914378	-0.7589986	-0.6741149	1.0212337	A137	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.1729719
1177	3.7707099	-0.0817113	2.6755476	1.3676416	-0.6741149	1.0212337	A423	C55	1.4810668	0.0181922	2.3175726	2.6287019	0.1225346	-0.2170130	1.0072463
1187	0.8334330	-0.8904536	-0.2655468	1.3676416	0.4307274	1.0212337	A323	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.3620957
1188	-0.5590024	-0.8904536	-0.7836469	-0.0501185	0.4307274	1.0212337	A172	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.2243028
1196	1.4309333	-0.8904536	0.4940736	1.3676416	-0.6741149	1.0212337	A299	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.2377106
1197	0.6602445	-0.0817113	-0.7135281	-0.7589986	-0.6741149	1.0212337	A128	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.3868376
1200	-0.8118576	-0.8904536	-0.7135281	-0.7589986	-0.6741149	1.0212337	A72	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1656158
1206	-0.5607343	-1.2710382	-0.7758559	-0.0501185	-0.6741149	1.0212337	A79	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.2660686
1218	1.0066215	0.6794579	0.1434796	-0.0501185	0.4307274	1.0212337	A297	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.2771260
1220	-0.3511762	-0.8904536	-0.6356183	-0.0501185	0.4307274	1.0212337	A172	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.2055441
1221	1.1728825	-0.0817113	0.4940736	1.3676416	-0.6741149	1.0212337	A333	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.3070218
1228	0.1250921	0.6794579	-0.7758559	-0.7589986	0.4307274	1.0212337	A173	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.3213397
1242	-0.3858139	-0.8904536	-0.7758559	-0.7589986	-0.6741149	1.0212337	A88	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1265840
1247	2.3852019	0.6794579	0.1512706	-0.0501185	-0.6741149	1.0212337	A300	C219	1.9755430	0.5864499	0.2031375	-0.2014525	0.1203785	0.5809108	0.3234473
1253	-0.4741401	-0.0817113	-1.1926732	-1.1134387	-0.6741149	1.0212337	A91	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.2650090
1254	0.2445922	-0.8904536	-0.2850242	-0.0501185	2.6404120	1.0212337	A255	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.2192632
1259	0.9113679	0.6794579	0.0499878	-0.0501185	-0.6741149	1.0212337	A239	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.2297720
1269	0.1337515	-0.0817113	-0.2850242	-0.0501185	0.4307274	0.3221550	A238	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.2205069
1270	-0.2056979	-0.8904536	-1.1420319	-0.7589986	-0.6741149	0.3221550	A98	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1522240
1277	0.1337515	-0.8904536	0.0499878	-0.0501185	-0.6741149	0.3221550	A188	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.0905453
1282	-1.2604158	-1.2710382	-1.1926732	-1.1134387	-0.6741149	0.3221550	A27	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.2370416
1283	0.4870561	-0.0817113	-0.2850242	-0.0501185	0.4307274	0.3221550	A252	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.2420173
1285	-0.3788864	0.6794579	-0.9472574	-0.7589986	-0.6741149	0.3221550	A125	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.1739817
1287	0.6515851	-0.0817113	0.0499878	-0.0501185	-0.6741149	0.3221550	A221	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.2315532
1288	-0.8118576	-0.0817113	-0.7836469	-0.7589986	-0.6741149	0.3221550	A94	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.2307387
1298	-0.5001183	0.6794579	-0.7914378	-0.7589986	0.4307274	0.3221550	A197	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.2927816
1302	-0.4221835	-1.2710382	-1.1420319	-0.7589986	-0.6741149	0.3221550	A60	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1520934
1303	-0.7079445	-0.0817113	-0.7914378	-0.7589986	0.4307274	0.3221550	A149	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.3177012
1305	0.0454254	-0.8904536	0.0499878	-0.0501185	-0.6741149	0.3221550	A188	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.0758243
1310	-1.4249449	-1.2710382	-0.9472574	-0.7589986	0.4307274	0.3221550	A76	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.3429802
1311	-0.0325094	-0.0817113	-0.7135281	-0.0501185	0.4307274	0.3221550	A191	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.3196344
1320	-0.9053794	-0.8904536	-1.1926732	-1.1134387	-0.6741149	0.3221550	A45	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.2339490
1329	-0.6473286	-1.2710382	-0.7758559	-0.7589986	-0.6741149	0.3221550	A87	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1285448
1336	3.2511444	0.6794579	0.3382540	1.3676416	2.6404120	0.3221550	A426	C96	2.0782294	0.7478725	0.1122044	0.7127714	2.6404120	0.5611990	0.3935489
1348	-0.9053794	-1.2710382	-0.7758559	-0.7589986	-0.6741149	0.3221550	A55	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1715532
1367	0.4350995	-0.8904536	-0.6550957	-0.0501185	-0.6741149	0.3221550	A175	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.2582839
1375	-0.3009516	-0.8904536	-0.7758559	-0.7589986	-0.6741149	0.3221550	A109	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1055158
1377	0.0454254	-0.0817113	-0.7758559	-0.7589986	-0.6741149	0.3221550	A147	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.2708561
1382	0.6256068	-0.8904536	-0.2850242	-0.7589986	-0.6741149	0.3221550	A144	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.3224593
1383	0.2186139	-0.8904536	-1.1420319	-0.7589986	-0.6741149	0.3221550	A98	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.2229426
1387	1.6907161	0.6794579	0.0421969	1.3676416	0.4307274	0.3221550	A355	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.3025392
1388	0.1926356	-0.8904536	-0.2850242	-0.0501185	2.6404120	0.3221550	A255	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.1993018
1390	-1.0872273	-0.8904536	-1.1926732	-1.1134387	0.4307274	0.3221550	A40	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.3904060
1393	0.4853242	-0.0817113	-0.7135281	-0.7589986	-0.6741149	0.3221550	A147	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.3545605
1396	-1.0716404	-1.2710382	-1.1420319	-0.7589986	-0.6741149	0.3221550	A36	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.2251638
1413	-0.8984519	0.6794579	-0.9472574	-0.7589986	-0.6741149	0.3221550	A125	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.2203138
1414	-2.1107713	-0.8904536	-1.2978514	-1.1134387	-0.6741149	0.3221550	A14	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.3791820
1434	-0.6473286	-0.8904536	-1.1926732	-1.1134387	-0.6741149	0.3221550	A64	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1909405
1440	0.4714691	-0.0817113	0.0499878	-0.0501185	-0.6741149	0.3221550	A221	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.2015339
1441	4.8167683	0.6794579	0.4356413	-0.0501185	2.6404120	0.3221550	A394	C96	2.0782294	0.7478725	0.1122044	0.7127714	2.6404120	0.5611990	0.6887207
1443	1.3374115	-0.0817113	0.4473277	1.3676416	0.4307274	0.3221550	A347	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.3305615
1451	1.2577448	-0.8904536	0.4473277	1.3676416	-0.6741149	0.3221550	A309	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.1505595
1453	0.6446576	-1.2710382	0.4473277	1.3676416	-0.6741149	0.3221550	A285	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.1817453
1454	-0.7772199	-0.8904536	-0.9472574	-0.7589986	-0.6741149	0.3221550	A92	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1126131
1455	1.3460710	0.6794579	0.0421969	1.3676416	0.4307274	0.3221550	A355	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.2450983
1459	0.8178461	-0.0817113	-0.2850242	-0.0501185	0.4307274	0.3221550	A252	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.2971490
1461	1.1798100	-0.0817113	-0.3629340	-0.0501185	0.4307274	0.3221550	A252	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.3704613
1480	1.6041218	-0.0817113	0.4473277	1.3676416	-0.6741149	0.3221550	A326	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.3206087
1483	1.3460710	0.6794579	0.4473277	1.3676416	-0.6741149	0.3221550	A354	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.2430285
1486	-0.2143573	0.6794579	-1.1926732	-1.1134387	-0.6741149	0.3221550	A140	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.2728719
1491	1.5106000	0.6794579	0.4473277	1.3676416	0.4307274	0.3221550	A373	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.2325647
1496	0.8178461	-0.8904536	0.4473277	1.3676416	0.4307274	0.3221550	A315	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.2046355
1497	1.1728825	-0.0817113	0.4473277	1.3676416	-0.6741149	0.3221550	A326	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.2487355
1500	-0.5676619	-0.8904536	-0.7758559	-0.7589986	-0.6741149	0.3221550	A92	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.0793166
1502	0.6533170	-0.8904536	0.4473277	1.3676416	-0.6741149	0.3221550	A294	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.1168713
1504	-0.2126255	-0.8904536	-0.2850242	-0.0501185	0.4307274	0.3221550	A181	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.1953703
1507	5.5095223	0.6794579	3.0650965	4.2031619	2.6404120	0.8195764	A440	B12	5.5095223	0.6794579	3.0650965	4.2031619	2.6404120	0.4969247	0.0537753
1508	-0.2212849	-0.8904536	-0.7758559	-0.7589986	0.4307274	0.8195764	A122	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.1911115
1510	-0.0394370	-0.8904536	-0.7836469	-0.7589986	2.6404120	0.8195764	A11	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.2812271
1511	0.6446576	0.6794579	0.0499878	-0.0501185	0.4307274	0.8195764	A277	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.1676072
1514	-0.8811330	-1.2710382	-1.1420319	-0.7589986	-0.6741149	0.8195764	A39	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1740115
1515	0.2186139	-0.0817113	-0.2850242	-0.0501185	0.4307274	0.8195764	A238	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.1781350
1519	-0.0480964	-0.8904536	0.0499878	-0.0501185	-0.6741149	0.8195764	A168	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.0756235
1525	2.0215061	0.6794579	3.7273297	-0.0501185	-0.6741149	0.8195764	A410	C219	1.9755430	0.5864499	0.2031375	-0.2014525	0.1203785	0.5809108	0.8079427
1527	-1.4249449	-0.8904536	-0.7836469	-0.7589986	-0.6741149	0.8195764	A54	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1034432
1528	0.9113679	-1.2710382	0.4473277	1.3676416	-0.6741149	0.8195764	A290	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.1731466
1530	0.1337515	-0.8904536	0.0499878	-0.0501185	-0.6741149	0.8195764	A189	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.1018743
1538	-0.8984519	0.6794579	-0.9472574	-0.7589986	-0.6741149	0.8195764	A125	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.1898280
1539	-1.4249449	-1.2710382	-1.1926732	-1.1134387	-0.6741149	0.8195764	A18	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1781120
1555	0.2532516	-0.8904536	-0.7836469	-0.7589986	-0.6741149	0.8195764	A106	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1981869
1558	0.6446576	-1.2710382	0.4473277	1.3676416	-0.6741149	0.8195764	A290	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.1986311
1563	0.2705704	-0.8904536	-1.1420319	-0.7589986	-0.6741149	0.8195764	A97	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.2332044
1570	-0.0480964	-0.0817113	-0.7758559	-0.7589986	-0.6741149	0.8195764	A128	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.2247832
1576	-0.9053794	-1.2710382	-0.7758559	-0.7589986	-0.6741149	0.8195764	A56	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1536080
1577	-0.2126255	0.6794579	-0.2850242	-0.7589986	0.4307274	0.8195764	A173	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.2622111
1581	-0.3944734	0.6794579	-1.1926732	-1.1134387	-0.6741149	0.8195764	A114	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.2123667
1586	0.1320196	-0.8904536	0.0499878	-0.0501185	-0.6741149	0.8195764	A189	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.1015856
1590	1.6041218	0.6794579	0.4473277	1.3676416	-0.6741149	0.8195764	A353	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.2438723
1594	0.3069400	-0.0817113	-0.2850242	-0.7589986	2.6404120	0.8195764	A320	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.1853942
1596	-0.7252634	-0.8904536	-1.1420319	-0.7589986	-0.6741149	0.8195764	A61	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1380184
1602	-0.9937055	-1.2710382	-1.1926732	-1.1134387	-0.6741149	0.8195764	A18	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1985897
1603	0.3918024	-0.8904536	0.0499878	-0.0501185	-0.6741149	0.8195764	A189	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.1448827
1617	0.8438243	0.6794579	0.5135511	-0.0501185	0.4307274	0.8195764	A277	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.2780622
1624	-1.5981334	-1.2710382	-0.9472574	-0.7589986	-0.6741149	0.8195764	A22	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1311740
1626	-0.2126255	-0.0817113	-0.7758559	-0.7589986	-0.6741149	0.8195764	A128	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.1973617
1633	0.1320196	-0.0817113	-0.7758559	-0.7589986	-0.6741149	0.8195764	A128	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.2548026
1642	0.9633244	-0.8904536	-0.2850242	-0.7589986	-0.6741149	0.8195764	A144	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.3900745
1645	-0.7079445	-0.0817113	-0.7914378	-0.7589986	0.4307274	0.8195764	A149	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.3074258
1649	-0.7495098	-0.8904536	-0.2850242	-0.7589986	0.4307274	0.8195764	A141	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.1619970
1659	1.6907161	0.6794579	0.4473277	1.3676416	-0.6741149	0.8195764	A353	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.2583046
1669	1.5106000	0.6794579	0.4473277	1.3676416	-0.6741149	0.8195764	A353	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.2282853
1670	0.9113679	-0.8904536	0.4473277	1.3676416	-0.6741149	0.8195764	A288	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.1097159
1671	0.8853896	0.6794579	-0.6550957	-0.7589986	0.4307274	0.8195764	A262	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.3540595
1681	0.3069400	0.6794579	-0.2850242	-0.0501185	0.4307274	0.8195764	A247	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.1151887
1683	-1.2604158	-1.2710382	-1.1926732	-1.1134387	-0.6741149	0.8195764	A18	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1541380
1688	-0.5520749	-0.0817113	-0.2850242	-0.7589986	-0.6741149	0.8195764	A132	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.2400595
1692	0.0454254	-0.8904536	0.0499878	-0.0501185	-0.6741149	0.8195764	A168	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.0871532
1695	-0.5590024	0.6794579	-1.1926732	-1.1134387	-0.6741149	0.8195764	A95	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.2047218
1697	-0.5590024	-1.2710382	-0.9472574	-0.7589986	2.6404120	0.8195764	A11	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.4585205
1704	2.4787237	0.6794579	0.1434796	-0.0501185	0.4307274	0.8195764	A329	C219	1.9755430	0.5864499	0.2031375	-0.2014525	0.1203785	0.5809108	0.2260325
1728	-1.4180174	-0.8904536	-0.7836469	-0.7589986	-0.6741149	0.8195764	A54	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1022886
1729	-0.3858139	0.6794579	-0.2850242	-0.7589986	-0.6741149	0.8195764	A154	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.2179917
1731	0.7901359	-0.8904536	-0.6550957	-0.0501185	-0.6741149	0.8195764	A175	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.3287856
1742	-0.3944734	-0.8904536	-0.7836469	-0.7589986	-0.6741149	0.8195764	A99	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.0902327
1745	1.3374115	-0.0817113	0.4473277	1.3676416	-0.6741149	0.8195764	A333	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.2930428
1756	1.6976436	0.6794579	0.1434796	1.3676416	0.4307274	0.8195764	A359	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.2446486
1759	-0.7425822	-0.8904536	-0.6356183	-0.7589986	-0.6741149	0.8195764	A83	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1334453
1771	-0.1277631	-0.8904536	-0.7758559	-0.7589986	-0.6741149	0.8195764	A106	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1359830
1772	-1.1755535	-1.2710382	-0.7836469	-0.7589986	-0.6741149	0.8195764	A35	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1072805
1774	0.8334330	-0.8904536	-0.6745732	-0.7589986	-0.6741149	0.8195764	A144	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.3130628
1784	-1.3314231	-1.2710382	-0.7836469	-0.7589986	-0.6741149	0.8195764	A35	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1015238
1798	-1.5981334	-1.2710382	-0.7836469	-0.7589986	-0.6741149	0.4969247	A37	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1997508
1800	-0.9140388	-1.2710382	-0.7836469	-0.7589986	-0.6741149	0.4969247	A55	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1425697
1811	-0.4395024	-1.2710382	-1.1420319	-0.7589986	-0.6741149	0.4969247	A60	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1200787
1813	-0.0480964	-0.0817113	-1.1926732	-1.1134387	-0.6741149	0.4969247	A91	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.3037644
1818	2.2968758	0.6794579	-0.2850242	1.3676416	2.6404120	0.4969247	A413	C96	2.0782294	0.7478725	0.1122044	0.7127714	2.6404120	0.5611990	0.2339057
1819	-0.5070459	0.6794579	-0.2850242	-0.7589986	0.4307274	0.4969247	A233	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.3103811
1824	-0.6802344	0.6794579	-0.2850242	-0.7589986	-0.6741149	0.4969247	A154	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.2304664
1826	0.0454254	-0.0817113	-0.7758559	-0.7589986	-0.6741149	0.4969247	A147	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.2417278
1832	-0.2056979	-0.8904536	-1.1420319	-0.7589986	-0.6741149	0.4969247	A98	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1230957
1845	-0.9850461	-1.2710382	-1.1420319	-0.7589986	-0.6741149	0.4969247	A36	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1865353
1858	0.4870561	0.6794579	0.0421969	-0.0501185	0.4307274	0.4969247	A277	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.1391417
1865	-0.0861979	-0.8904536	-0.7836469	-0.7589986	-0.6741149	0.4969247	A118	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1108814
1871	0.8091866	0.6794579	0.5135511	-0.0501185	-0.6741149	0.4969247	A253	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.2568985
1872	-0.3009516	0.6794579	-1.1926732	-1.1134387	-0.6741149	0.4969247	A112	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.2293112
1875	0.1164327	0.6794579	-0.2850242	-0.0501185	0.4307274	0.4969247	A247	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.1256840
1876	0.2532516	-0.8904536	-0.7836469	-0.7589986	-0.6741149	0.4969247	A118	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1674563
1877	-0.6473286	-1.2710382	-0.7758559	-0.7589986	-0.6741149	0.4969247	A87	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.0994165
1889	-0.7252634	-0.8904536	-0.7135281	-0.7589986	-0.6741149	0.4969247	A92	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.0868432
1890	0.3831430	-0.0817113	-0.2850242	-0.0501185	2.6404120	0.4969247	A320	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.1790190
1892	-0.9053794	-1.2710382	-0.7758559	-0.7589986	-0.6741149	0.4969247	A55	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1424249
1897	1.6041218	-0.0817113	0.4473277	1.3676416	-0.6741149	0.4969247	A326	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.2914804
1901	-0.0567558	-1.2710382	0.4473277	-0.0501185	-0.6741149	0.4969247	A160	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.1438113
1910	0.4853242	-0.0817113	-0.3629340	-0.0501185	0.4307274	0.4969247	A252	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.2255854
1919	-0.8118576	-0.0817113	-0.6550957	-0.7589986	0.4307274	0.4969247	A149	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.2831681
1922	2.0301655	0.6794579	0.4473277	1.3676416	-0.6741149	0.4969247	A368	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.3279160
1929	0.2445922	-0.8904536	-0.6550957	-0.0501185	-0.6741149	0.4969247	A175	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.1974044
1930	-0.2922922	-0.8904536	-0.7836469	-0.7589986	-0.6741149	0.4969247	A109	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.0765323
1937	-0.0480964	-0.8904536	-0.7758559	-0.7589986	-0.6741149	0.4969247	A118	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1185301
1940	0.2186139	0.6794579	-0.7758559	-0.7589986	-0.6741149	0.4969247	A179	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.2382820
1941	-0.9053794	-0.8904536	-0.2850242	-0.7589986	0.4307274	0.4969247	A141	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.1691224
1944	0.1406791	0.6794579	-1.1420319	-0.7589986	-0.6741149	0.4969247	A140	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.2639100
1965	2.0457525	0.6794579	0.4434322	-0.7589986	0.4307274	0.4969247	A329	C219	1.9755430	0.5864499	0.2031375	-0.2014525	0.1203785	0.5809108	0.2258989
1971	-1.2604158	-1.2710382	-1.1926732	-1.1134387	0.4307274	0.4969247	A15	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.3656806
1975	-0.8984519	-1.2710382	-0.7836469	-0.7589986	-0.6741149	0.4969247	A55	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1399719
1979	0.4714691	-0.0817113	-0.7758559	-0.7589986	-0.6741149	0.4969247	A147	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.3127351
1986	-0.3858139	-1.2710382	0.0499878	-0.0501185	-0.6741149	0.4969247	A160	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.1326269
1998	0.1337515	0.6794579	-0.2850242	-0.0501185	0.4307274	0.4969247	A247	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.1227975
2007	0.8178461	-0.8904536	0.0499878	-0.0501185	-0.6741149	0.4969247	A188	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.1754328
2010	1.0914839	0.6794579	-0.6550957	-0.7589986	0.4307274	0.4969247	A262	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.3875085
2014	-1.2517564	-0.8904536	-0.7836469	-0.7589986	-0.6741149	0.4969247	A63	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1346877
2015	0.9113679	-1.2710382	0.4473277	1.3676416	-0.6741149	0.4969247	A290	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.1271325
2019	-1.2517564	-0.8904536	-0.7836469	-0.7589986	-0.6741149	0.4969247	A63	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1346877
2020	-0.7408504	-1.2710382	-1.1926732	-1.1134387	-0.6741149	0.4969247	A27	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.2133495
2023	-0.5676619	-0.0817113	-1.1926732	-1.1134387	0.4307274	0.4969247	A68	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.3874417
2025	-0.8811330	-1.2710382	-1.1420319	-0.7589986	-0.6741149	0.4969247	A60	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1692164
2040	0.4108531	-0.8904536	0.5135511	-0.0501185	-0.6741149	0.4969247	A202	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.1846652
2048	-0.2576545	-0.8904536	-0.2850242	-0.7589986	-0.6741149	0.7120258	A127	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1782146
2054	-0.7166040	-1.2710382	-1.1420319	-0.7589986	-0.6741149	0.7120258	A57	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1546005
2056	-1.1149375	-1.2710382	-0.7836469	-0.7589986	-0.6741149	0.7120258	A55	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1353083
2061	-0.3788864	-0.8904536	-0.6356183	-0.7589986	-0.6741149	0.7120258	A99	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.0995769
2066	2.9116949	0.6794579	0.4434322	1.3676416	2.6404120	0.7120258	A413	C96	2.0782294	0.7478725	0.1122044	0.7127714	2.6404120	0.5611990	0.3398008
2071	-0.0325094	-0.0817113	-0.2850242	-0.0501185	0.4307274	0.7120258	A238	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.2020638
2090	0.7381794	0.6794579	0.0499878	-0.0501185	-0.6741149	0.7120258	A253	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.1493726
2093	-0.4741401	-1.2710382	-0.7758559	-0.7589986	-0.6741149	0.7120258	A70	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.0962787
2094	0.7554982	-0.8904536	-0.2850242	-0.7589986	-0.6741149	0.7120258	A144	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.3375118
2097	5.5095223	0.6794579	3.0650965	4.2031619	2.6404120	0.7120258	A440	B12	5.5095223	0.6794579	3.0650965	4.2031619	2.6404120	0.4969247	0.0358502
2102	1.2577448	-0.0817113	0.4473277	1.3676416	-0.6741149	0.7120258	A314	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.2618399
2103	0.9823751	-0.8904536	2.5197280	-0.0501185	-0.6741149	0.7120258	A390	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.6368139
2106	0.1770487	-0.8904536	0.4473277	-0.0501185	-0.6741149	0.7120258	A202	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.1571928
2110	0.9113679	-1.2710382	0.4473277	1.3676416	-0.6741149	0.7120258	A290	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.1552215
2113	-0.3355893	-1.2710382	-0.9472574	-0.7589986	-0.6741149	0.7120258	A84	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1177407
2114	-0.7252634	-1.2710382	0.0421969	-0.7589986	-0.6741149	0.7120258	A108	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.2615533
2116	-0.5676619	-0.8904536	-0.7758559	-0.7589986	0.4307274	0.7120258	A101	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.1470683
2118	0.1250921	-0.8904536	-0.7758559	-0.7589986	-0.6741149	0.7120258	A118	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1602004
2123	0.0454254	-1.2710382	0.0499878	-0.0501185	-0.6741149	0.7120258	A159	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.1104025
2124	-0.0480964	-0.8904536	-0.7758559	-0.7589986	-0.6741149	0.7120258	A106	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1313356
2126	0.4714691	-0.8904536	0.0499878	-0.0501185	-0.6741149	0.7120258	A189	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.1402354
2129	-0.5520749	-0.8904536	-0.6550957	-0.7589986	0.4307274	0.7120258	A101	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.1243438
2133	0.7087373	0.6794579	0.0421969	-0.0501185	0.4307274	0.7120258	A277	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.1590635
2134	1.3460710	0.6794579	-0.2850242	1.3676416	0.4307274	0.7120258	A355	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.2395454
2142	1.3529985	0.6794579	-0.2850242	-0.0501185	0.4307274	0.7120258	A280	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.2716066
2145	-0.4654806	-0.0817113	-0.6550957	-0.7589986	0.4307274	0.7120258	A149	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.2288153
2146	-0.2749733	-0.8904536	-0.7836469	-0.7589986	-0.6741149	0.7120258	A99	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.0922243
2149	3.0779559	0.6794579	2.2859986	1.3676416	-0.6741149	0.7120258	A423	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.7780313
2152	0.9823751	-0.8904536	0.4940736	-0.0501185	2.6404120	0.7120258	A255	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.4205421
2156	0.4801285	0.6794579	0.0421969	-0.0501185	0.4307274	0.7120258	A277	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.1209621
2157	0.0869906	-0.8904536	-0.2850242	-0.7589986	-0.6741149	0.7120258	A144	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.2260938
2158	-1.2517564	-0.8904536	-0.7836469	-0.7589986	-0.6741149	0.7120258	A63	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.0988375
2161	0.2272733	0.6794579	-0.2850242	-0.7589986	-0.6741149	0.7120258	A195	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.2049874
2164	-1.2604158	-1.2710382	-1.1926732	-1.1134387	0.4307274	0.7120258	A15	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.3298305
2179	1.3287521	0.6794579	0.4940736	-0.0501185	2.6404120	0.7120258	A357	C96	2.0782294	0.7478725	0.1122044	0.7127714	2.6404120	0.5611990	0.3522463
2182	-0.3009516	0.6794579	-1.1926732	-1.1134387	-0.6741149	0.7120258	A114	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.2100286
2183	-0.0394370	-0.8904536	0.0499878	-0.0501185	-0.6741149	0.7120258	A168	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.0562552
2188	-0.4204516	0.6794579	-0.2850242	-0.7589986	0.4307274	0.7120258	A173	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.2789237
2190	-0.5676619	-0.8904536	-1.1926732	-1.1134387	-0.6741149	0.7120258	A48	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1613400
2193	0.3623603	-0.0817113	0.0421969	-0.0501185	0.4307274	0.7120258	A238	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.1699152
2205	2.9047674	-0.0817113	2.2859986	1.3676416	-0.6741149	0.7120258	A423	C55	1.4810668	0.0181922	2.3175726	2.6287019	0.1225346	-0.2170130	0.7569878
2207	1.1642231	-0.0817113	0.4473277	1.3676416	0.4307274	0.7120258	A347	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.2942429
2209	-1.2517564	-0.8904536	-1.1926732	-1.1134387	-0.6741149	0.7120258	A31	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1598387
2215	-0.8984519	0.6794579	-0.6550957	-0.7589986	-0.6741149	0.7120258	A125	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.1858747
2218	-1.0716404	-1.2710382	-0.7836469	-0.7589986	-0.6741149	0.7120258	A55	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1425245
2221	-0.6386691	0.6794579	-0.6550957	-0.7589986	0.4307274	0.7120258	A173	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.2901861
2228	-0.5590024	-0.8904536	-0.7758559	-0.7589986	-0.6741149	0.7120258	A90	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.0615506
2230	-1.5981334	-1.2710382	-0.7758559	-0.7589986	-0.6741149	0.7120258	A22	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1651991
2235	-1.4595826	-1.2710382	-1.1420319	-0.7589986	-0.6741149	0.7120258	A26	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1584697
2248	-1.2448289	-0.8904536	-0.6550957	-0.7589986	-0.6741149	0.7120258	A63	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1214173
2254	2.5912962	0.6794579	0.4434322	-0.0501185	0.4307274	0.7120258	A360	C219	1.9755430	0.5864499	0.2031375	-0.2014525	0.1203785	0.5809108	0.2569757
2259	-0.7252634	-0.8904536	-1.1420319	-0.7589986	-0.6741149	0.7120258	A59	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1200933
2261	0.1337515	-0.0817113	0.0421969	-0.0501185	0.4307274	0.7120258	A238	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.1691874
2263	-0.9175026	-1.2710382	-0.7836469	-0.7589986	-0.6741149	0.7120258	A70	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1559525
2264	-0.9053794	-0.8904536	-0.2850242	-0.0501185	-0.6741149	0.7120258	A115	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.2564143
2276	-0.1710602	-1.2710382	-1.1420319	-0.7589986	-0.6741149	0.7120258	A57	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1776246
2283	1.3287521	0.6794579	2.5197280	-0.0501185	-0.6741149	0.7120258	A410	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.6594248
2289	-0.2039660	-1.2710382	0.0421969	-0.7589986	2.6404120	0.7120258	A11	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.3553920
2295	-1.5912058	-1.2710382	-1.1420319	-0.7589986	-0.6741149	0.7120258	A26	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1804069
2296	1.6993755	0.6794579	-0.2850242	1.3676416	0.4307274	0.7120258	A355	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.2984295
2300	-0.4741401	-0.0817113	-1.1926732	-1.1134387	-0.6741149	0.7120258	A91	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.2134744
2303	0.9113679	-0.8904536	0.4473277	1.3676416	-0.6741149	0.7120258	A288	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.0917908
2307	0.8334330	0.6794579	-0.6550957	-0.0501185	0.4307274	0.7120258	A262	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.2466910
2308	-0.1277631	-0.0817113	-0.7758559	-0.7589986	-0.6741149	0.7120258	A128	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.1935803
2316	-0.7789518	-0.8904536	-1.1420319	-0.7589986	-0.6741149	0.7120258	A59	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1290414
2321	-0.1277631	-0.8904536	-0.7758559	-0.7589986	-0.6741149	0.7120258	A99	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1180579
2323	0.1250921	0.6794579	-0.7758559	-0.7589986	0.4307274	-0.0811597	A197	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.3831775
2326	-0.9937055	-1.2710382	-1.1926732	-1.1134387	-0.6741149	-0.0811597	A27	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.3487124
2331	1.5175276	0.6794579	-0.2850242	-0.7589986	-0.6741149	-0.0811597	A209	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.4746053
2332	0.6446576	-0.8904536	0.0499878	-0.0501185	-0.6741149	-0.0811597	A217	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.2429154
2333	-0.6473286	-0.0817113	-1.1926732	-1.1134387	-0.6741149	-0.0811597	A113	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.3494584
2334	0.9910346	-0.8904536	0.4473277	1.3676416	0.4307274	-0.0811597	A323	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.2885126
2335	1.0845564	-0.8904536	0.4473277	1.3676416	-0.6741149	-0.0811597	A310	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.1889139
2336	2.5653180	0.6794579	0.4434322	1.3676416	2.6404120	-0.0811597	A413	C96	2.0782294	0.7478725	0.1122044	0.7127714	2.6404120	0.5611990	0.3639933
2340	-1.0872273	-0.8904536	-1.1926732	-1.1134387	0.4307274	-0.0811597	A40	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.4352986
2351	0.2896212	0.6794579	0.0266149	-0.0501185	2.6404120	-0.0811597	A344	C142	0.1328959	0.6627507	0.4814828	-0.0248014	2.6404120	-0.9712527	0.2572851
2362	0.8178461	-0.0817113	0.0499878	-0.0501185	-0.6741149	-0.0811597	A248	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.3264825
2364	0.2982806	-0.0817113	-0.7758559	-0.7589986	-0.6741149	-0.0811597	A147	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.3802177
2380	0.3104038	0.6794579	-0.5577085	-0.7589986	-0.6741149	-0.0811597	A180	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.3513579
2396	-0.0325094	-0.8904536	-0.2850242	-0.0501185	2.6404120	-0.0811597	A249	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.3040451
2401	-0.3944734	-0.8904536	-1.1926732	-1.1134387	-0.6741149	-0.0811597	A64	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.2554941
2402	0.0714037	-0.8904536	-0.6550957	-0.7589986	-0.6741149	-0.0811597	A145	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.2549209
2404	0.8749983	-0.8904536	-0.2850242	-0.7589986	-0.6741149	-0.0811597	A145	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.4312437
2409	-1.5981334	-1.2710382	-1.1926732	-0.7589986	-0.6741149	-0.0811597	A23	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.3221993
2410	0.6498532	-0.0817113	-0.7836469	-0.7589986	-0.6741149	-0.0811597	A147	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.4375147
2419	0.8334330	0.6794579	0.4473277	-0.0501185	0.4307274	-0.0811597	A273	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.3607404
2420	-0.5364879	-0.8904536	-1.1420319	-0.7589986	-0.6741149	-0.0811597	A58	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1721726
2429	-1.0196838	-0.0817113	-0.6550957	-0.7589986	0.4307274	-0.0811597	A148	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.4141531
2436	0.0454254	-1.2710382	0.0499878	-0.0501185	-0.6741149	-0.0811597	A199	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.1842177
2440	-0.5607343	-0.0817113	-0.2850242	-0.7589986	0.4307274	-0.0811597	A148	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.3244839
2442	1.1261216	0.6794579	-0.2850242	-0.7589986	-0.6741149	-0.0811597	A209	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.4093710
2443	-0.8984519	-0.8904536	-1.1420319	-0.7589986	-0.6741149	-0.0811597	A58	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.2324999
2452	1.3460710	0.6794579	0.4473277	1.3676416	-0.6741149	-0.0811597	A354	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.3102476
2454	-1.0785679	-0.8904536	0.0266149	-0.7589986	-0.6741149	-0.0811597	A117	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.2827346
2456	1.3529985	0.6794579	0.1434796	1.3676416	0.4307274	-0.0811597	A373	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.2965916
2458	0.5649909	-0.0817113	0.0499878	-0.0501185	-0.6741149	-0.0811597	A248	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.2843400
2462	1.5227232	0.6794579	0.4473277	-0.0501185	0.4307274	-0.0811597	A297	C219	1.9755430	0.5864499	0.2031375	-0.2014525	0.1203785	0.5809108	0.3189619
2472	1.0066215	0.6794579	-0.2850242	1.3676416	0.4307274	-0.0811597	A355	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.4154493
2479	-0.6473286	-1.2710382	-0.7758559	-0.7589986	-0.6741149	-0.0811597	A110	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1957639
2491	-0.9053794	-1.2710382	-0.7758559	-0.7589986	-0.6741149	-0.0811597	A93	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.2387723
2493	-0.7252634	-0.8904536	-1.1420319	-0.7589986	-0.6741149	-0.0811597	A58	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.2036352
2494	-1.3729883	-1.2710382	-1.1420319	-0.7589986	-0.6741149	-0.0811597	A23	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.2762349
2498	0.1060414	-0.0817113	-0.2850242	-0.0501185	2.6404120	-0.0811597	A344	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.2723753
2510	-0.0394370	-0.8904536	0.0499878	-0.0501185	-0.6741149	-0.0811597	A199	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.1300704
2532	0.2186139	-0.8904536	0.0499878	-0.0501185	-0.6741149	-0.0811597	A199	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.1719081
2540	0.1926356	0.6794579	-0.7836469	-0.7589986	-0.6741149	0.9405708	A155	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.2514619
2549	1.5106000	0.6794579	0.4473277	1.3676416	0.4307274	0.9405708	A359	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.2105657
2551	1.0066215	-0.0817113	-0.7135281	-0.0501185	0.4307274	0.9405708	A252	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.3919664
2555	1.5106000	0.6794579	0.4473277	1.3676416	-0.6741149	0.9405708	A353	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.2484510
2565	-0.2143573	-0.0817113	0.0421969	-0.7589986	-0.6741149	0.9405708	A156	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.3505343
2566	-1.4180174	0.6794579	-0.5577085	-0.7589986	-0.6741149	0.9405708	A102	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.3267910
2568	1.1624912	-0.8904536	-0.2850242	-0.7589986	2.6404120	0.9405708	A4	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.3567298
2569	-1.1668940	-0.8904536	-1.1926732	-1.1134387	-0.6741149	0.9405708	A32	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1631116
2573	0.3069400	0.6794579	-0.2850242	-0.0501185	0.4307274	0.9405708	A247	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.1353544
2575	-1.5912058	-0.8904536	-0.7836469	-0.7589986	-0.6741149	0.9405708	A42	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1382076
2582	0.2186139	-0.8904536	0.0499878	-0.0501185	-0.6741149	0.9405708	A189	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.1361837
2591	-0.7321909	-0.0817113	-0.7758559	-0.7589986	-0.6741149	0.9405708	A103	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.2084393
2595	0.1320196	-0.0817113	0.0421969	-0.0501185	-0.6741149	0.9405708	A204	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.2261462
2601	-1.4699739	-1.2710382	-1.1420319	-0.7589986	-0.6741149	0.9405708	A26	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1493308
2603	0.3588966	-0.0817113	-0.7836469	-0.0501185	-0.6741149	0.9405708	A128	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.2866401
2604	-1.2534883	-0.8904536	-0.6745732	-0.7589986	0.4307274	0.9405708	A101	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.2636243
2607	0.5043749	-0.0817113	-0.2850242	-0.7589986	0.4307274	0.9405708	A185	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.3176254
2609	1.6041218	0.6794579	0.4473277	1.3676416	-0.6741149	0.9405708	A353	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.2640380
2611	0.4801285	-1.2710382	0.4473277	1.3676416	-0.6741149	0.9405708	A274	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.2462184
2612	-1.0872273	-1.2710382	-0.7758559	-0.7589986	-0.6741149	0.9405708	A56	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1303543
2613	1.0845564	-0.8904536	0.4473277	1.3676416	-0.6741149	0.9405708	A299	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.1587463
2614	0.0714037	-1.2710382	-0.7836469	-0.7589986	2.6404120	0.9405708	A4	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.3463502
2615	1.0862882	0.6794579	0.0421969	-0.0501185	2.6404120	0.9405708	A357	C96	2.0782294	0.7478725	0.1122044	0.7127714	2.6404120	0.5611990	0.3787709
2637	1.8639046	0.6794579	0.4473277	1.3676416	-0.6741149	0.9405708	A353	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.3073351
2638	0.3502371	-0.0817113	0.4473277	-0.0501185	-0.6741149	0.9405708	A204	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.2572984
2648	-0.4550893	0.6794579	0.0266149	-0.7589986	-0.6741149	0.9405708	A154	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.2785513
2649	-0.2212849	-1.2710382	0.0499878	-0.0501185	-0.6741149	0.9405708	A159	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.1658284
2651	0.7381794	-1.2710382	0.4473277	1.3676416	-0.6741149	0.9405708	A290	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.2032099
2652	1.5088682	0.6794579	0.0421969	-0.0501185	-0.6741149	0.9405708	A251	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.3146131
2654	0.9113679	-1.2710382	0.4473277	1.3676416	-0.6741149	0.9405708	A290	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.1933124
2659	-1.0370027	-1.2710382	-1.1420319	-0.7589986	0.4307274	0.9405708	A38	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.3128548
2660	0.3052081	-0.8904536	0.0499878	-0.0501185	-0.6741149	0.9405708	A189	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.1506161
2662	-0.4827995	-0.8904536	-0.7836469	-0.7589986	-0.6741149	0.9405708	A88	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.0956775
2676	0.9546650	0.6794579	-0.2850242	-0.0501185	-0.6741149	0.9405708	A251	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.2374489
2679	0.6446576	-1.2710382	0.4473277	1.3676416	-0.6741149	0.9405708	A290	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.2187969
2680	2.4960426	0.6794579	0.0421969	-0.0501185	2.6404120	0.9405708	A394	C96	2.0782294	0.7478725	0.1122044	0.7127714	2.6404120	0.5611990	0.2830828
2681	0.7381794	0.6794579	0.0499878	-0.0501185	-0.6741149	0.9405708	A253	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.1874635
2684	0.7399113	0.6794579	0.0421969	-0.0501185	2.6404120	0.9405708	A336	C96	2.0782294	0.7478725	0.1122044	0.7127714	2.6404120	0.5611990	0.4365004
2694	1.0412592	-0.0817113	-0.2850242	-0.0501185	0.4307274	0.9405708	A252	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.3263221
2695	0.6775634	-0.8904536	-0.7836469	-0.7589986	2.6404120	0.9405708	A4	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.3292076
2701	1.0066215	0.6794579	-0.2850242	1.3676416	0.4307274	0.9405708	A355	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.3262312
2713	-1.0785679	-0.8904536	-0.2850242	-0.0501185	-0.6741149	0.9405708	A115	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.3180819
2715	0.9546650	-0.0817113	-0.2850242	-0.0501185	0.4307274	0.9405708	A252	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.3118897
2719	-0.6473286	-0.8904536	-0.7758559	-0.7589986	-0.6741149	0.9405708	A72	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1143625
2720	-1.0802998	-0.8904536	-0.7836469	-0.7589986	-0.6741149	0.9405708	A53	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1165428
2725	0.3623603	0.6794579	0.0421969	-0.0501185	0.4307274	0.9405708	A277	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.1394249
2727	0.8178461	-0.8904536	0.4473277	1.3676416	0.4307274	0.9405708	A323	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.2416870
2732	-1.5132710	-1.2710382	-1.1926732	-1.1134387	-0.6741149	0.9405708	A18	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1998873
2737	1.1798100	0.6794579	-0.7836469	-0.7589986	2.6404120	0.9405708	A342	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.5311990
2755	0.4870561	-0.8904536	-0.7836469	-0.7589986	2.6404120	0.9405708	A4	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.2974564
2766	0.9996940	0.6794579	-0.2850242	-0.0501185	0.4307274	0.9405708	A280	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.2508134
2768	0.4801285	0.6794579	0.0499878	-0.0501185	-0.6741149	0.9405708	A239	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.1444550
2771	-0.7321909	-0.0817113	-0.2850242	-0.7589986	-0.6741149	0.9405708	A132	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.2902446
2784	0.0021283	-0.8904536	-0.2850242	-0.7589986	-0.6741149	0.9405708	A106	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.2500409
2794	0.1753168	-0.8904536	-0.2850242	-0.7589986	-0.6741149	0.9405708	A144	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.2789057
2796	0.9113679	0.6794579	0.0499878	-0.0501185	-0.6741149	0.9405708	A253	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.2163282
2814	0.7814765	-0.0817113	-0.2850242	-0.0501185	-0.6741149	0.9405708	A221	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.2576381
2816	1.3460710	0.6794579	0.4473277	1.3676416	-0.6741149	0.9405708	A353	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.2210295
2818	0.2186139	-0.8904536	0.0499878	-0.0501185	-0.6741149	0.9405708	A189	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.1361837
2821	1.3460710	0.6794579	-0.2850242	1.3676416	0.4307274	0.9405708	A355	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.2776362
2830	-0.9053794	-0.8904536	-0.7758559	-0.7589986	-0.6741149	0.9405708	A72	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1469947
2831	-0.9746548	-0.0817113	-0.2850242	-0.7589986	0.4307274	0.6044753	A149	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.2801259
2839	-0.5590024	0.6794579	0.0460923	-0.0501185	0.4307274	0.6044753	A233	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.2158144
2843	-0.9053794	0.6794579	-1.1926732	-1.1134387	-0.6741149	0.6044753	A112	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.2458838
2844	0.6775634	-0.8904536	-0.7836469	-0.7589986	2.6404120	0.6044753	A4	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.2731917
2857	-1.2517564	-0.8904536	-0.7836469	-0.7589986	-0.6741149	0.6044753	A63	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1167626
2863	0.0817950	0.6794579	0.0460923	-0.0501185	2.6404120	0.6044753	A336	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.3474149
2868	-0.3788864	-1.2710382	-0.9472574	-0.7589986	-0.6741149	0.6044753	A84	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.0925994
2878	-0.3788864	0.6794579	0.1434796	-0.7589986	-0.6741149	0.6044753	A154	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.2739961
2895	-1.0785679	-0.8904536	-0.7758559	-0.7589986	-0.6741149	0.6044753	A63	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1302198
2897	-0.5243647	-0.8904536	0.0460923	-0.0501185	0.4307274	0.6044753	A176	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.1696533
2902	0.2965487	-0.8904536	-1.1420319	-0.7589986	2.6404120	0.6044753	A4	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.2694201
2904	-0.4741401	-0.8904536	-0.7758559	-0.7589986	-0.6741149	0.6044753	A90	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.0424033
2909	0.5043749	-0.0817113	-0.2850242	-0.7589986	0.4307274	0.6044753	A191	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.2786345
2912	0.5753822	0.6794579	-0.2850242	-0.0501185	0.4307274	0.6044753	A247	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.1411038
2914	0.2186139	-0.0817113	0.0499878	-0.0501185	-0.6741149	0.6044753	A204	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.1754271
2918	-0.4741401	-0.0817113	-0.7758559	-0.7589986	-0.6741149	0.6044753	A120	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.1372084
2920	-0.7321909	-0.0817113	0.0266149	-0.7589986	-0.6741149	0.6044753	A132	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.3054512
2923	1.2577448	0.6794579	0.4473277	1.3676416	-0.6741149	0.6044753	A353	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.2027162
2928	0.6446576	-0.8904536	0.4473277	1.3676416	-0.6741149	0.6044753	A264	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.0993502
2932	1.4309333	0.6794579	0.4473277	1.3676416	-0.6741149	0.6044753	A353	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.2101189
2937	0.2982806	-1.2710382	0.4473277	1.3676416	0.4307274	0.6044753	A307	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.3356961
2957	0.7381794	0.6794579	0.0499878	-0.0501185	-0.6741149	0.6044753	A253	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.1498783
2958	-0.9746548	0.6794579	-0.2850242	-0.7589986	-0.6741149	0.6044753	A154	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.2616114
2964	-0.8984519	-0.8904536	-1.1420319	-0.7589986	-0.6741149	0.6044753	A59	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1310330
2971	-0.5001183	-0.8904536	-0.7836469	-0.7589986	-0.6741149	0.6044753	A90	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.0367751
2983	-1.4336043	-0.8904536	-1.1926732	-1.1134387	0.4307274	0.6044753	A15	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.3595051
2988	-0.6906257	-0.8904536	-1.1420319	-0.7589986	-0.6741149	0.6044753	A75	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.0963953
2998	0.4801285	-0.8904536	0.4473277	1.3676416	-0.6741149	0.6044753	A264	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.1267717
3005	-0.0394370	-0.0817113	0.0266149	-0.0501185	0.4307274	0.6044753	A238	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.1945551
3013	1.0845564	-0.0817113	0.4473277	1.3676416	-0.6741149	0.6044753	A314	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.2150501
3020	-1.0802998	-0.8904536	-0.2850242	-0.7589986	0.4307274	0.6044753	A141	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.1812785
3021	-0.9053794	-0.8904536	-0.7758559	-0.7589986	-0.6741149	0.6044753	A77	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1013550
3030	-1.5981334	-0.8904536	-0.7758559	-0.7589986	-0.6741149	0.6044753	A54	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1694566
3031	0.3588966	0.6794579	-0.7836469	-0.0501185	0.4307274	0.6044753	A247	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.1881267
3033	-1.2517564	-0.8904536	-0.2850242	-0.7589986	-0.6741149	0.6044753	A89	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1998664
3037	-0.0325094	0.6794579	-0.2850242	-0.0501185	-0.6741149	0.6044753	A216	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.1821316
3039	-1.2517564	-0.0817113	-1.1926732	-1.1134387	-0.6741149	0.6044753	A50	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.3125542
3041	-0.5070459	-0.8904536	-0.7836469	-0.7589986	0.4307274	0.6044753	A122	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.1203390
3047	-0.3858139	-0.0817113	0.0421969	-0.0501185	-0.6741149	0.6044753	A204	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.2321485
3051	-0.9157707	-1.2710382	-0.7836469	-0.7589986	-0.6741149	0.6044753	A55	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1377388
3052	-0.4204516	-0.8904536	0.0421969	-0.0501185	-0.6741149	0.6044753	A157	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.1031311
3060	1.1624912	-0.8904536	-0.2850242	-0.7589986	2.6404120	0.6044753	A311	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.3007139
3089	-1.7713219	-1.2710382	-0.7758559	-0.7589986	-0.6741149	0.6044753	A22	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.2119890
3102	0.8178461	2.2969425	0.0499878	-0.0501185	-0.6741149	1.1422281	A317	C301	0.3539798	2.2969425	-0.1275540	-0.2934206	-0.2808659	0.8171839	0.2671672
3112	-0.2143573	1.1076156	-1.1926732	-1.1134387	-0.6741149	1.1422281	A30	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.3675209
3113	1.5088682	0.6794579	0.0421969	-0.0501185	-0.6741149	1.1422281	A251	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.3482226
3115	1.3027739	0.6794579	0.0266149	1.3676416	0.4307274	1.1422281	A359	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.2585422
3120	0.1337515	0.6794579	0.0421969	-0.0501185	0.4307274	1.1422281	A259	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.1723066
3121	0.5649909	1.1076156	0.0499878	-0.0501185	-0.6741149	1.1422281	A239	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.2635679
3125	-0.3788864	0.6794579	0.1434796	-0.7589986	-0.6741149	1.1422281	A154	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.3443388
3136	1.1884694	0.6794579	-0.2850242	-0.0501185	2.6404120	1.1422281	A357	C96	2.0782294	0.7478725	0.1122044	0.7127714	2.6404120	0.5611990	0.4498871
3138	0.0021283	-0.8904536	-0.2850242	-0.7589986	-0.6741149	1.1422281	A106	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.2836505
3141	-0.4827995	-0.8904536	-0.7836469	-0.7589986	-0.6741149	1.1422281	A88	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1292870
3143	1.5261870	2.2969425	0.4434322	1.3676416	0.4307274	1.1422281	A396	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.4122882
3157	2.7385064	0.6794579	0.4434322	-0.0501185	2.6404120	1.1422281	A394	C96	2.0782294	0.7478725	0.1122044	0.7127714	2.6404120	0.5611990	0.4006398
3160	1.0845564	0.6794579	0.4473277	1.3676416	-0.6741149	1.1422281	A338	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.2902449
3169	1.3529985	2.2969425	0.4434322	1.3676416	0.4307274	1.1422281	A396	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.3834234
3172	1.0845564	2.2969425	0.0499878	-0.0501185	-0.6741149	1.1422281	A317	C301	0.3539798	2.2969425	-0.1275540	-0.2934206	-0.2808659	0.8171839	0.3116190
3175	-0.6802344	0.6794579	0.0460923	-0.0501185	0.4307274	1.1422281	A234	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.3086202
3191	-0.2212849	2.2969425	-1.1926732	-1.1134387	0.4307274	1.1422281	A210	C301	0.3539798	2.2969425	-0.1275540	-0.2934206	-0.2808659	0.8171839	0.5828399
3194	1.0066215	-0.0817113	-0.2850242	-0.0501185	0.4307274	1.1422281	A252	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.3541587
3225	0.2186139	-0.0817113	0.0499878	-0.0501185	-0.6741149	1.1422281	A204	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.2466218
3227	0.6446576	-0.0817113	0.4473277	1.3676416	0.4307274	1.1422281	A347	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.4164810
3228	-1.5132710	-1.2710382	-1.1926732	-1.1134387	-0.6741149	1.1422281	A8	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.2334969
3231	2.2189410	2.2969425	2.2859986	1.3676416	0.4307274	1.1422281	A402	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.8348416
3246	0.7381794	1.1076156	0.0499878	-0.0501185	-0.6741149	1.1422281	A239	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.2924326
3254	-0.5676619	0.6794579	-0.7758559	-0.7589986	0.4307274	1.1422281	A173	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.3299253
3262	1.0412592	-0.0817113	-0.2850242	-0.0501185	0.4307274	1.1422281	A252	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.3599316
3265	0.3588966	-0.0817113	-0.7836469	-0.0501185	2.6404120	1.1422281	A320	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.3032008
3268	1.3460710	2.2969425	0.4473277	1.3676416	-0.6741149	1.1422281	A396	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.4208034
3270	2.1150279	0.6794579	-0.2850242	-0.0501185	2.6404120	1.1422281	A385	C96	2.0782294	0.7478725	0.1122044	0.7127714	2.6404120	0.5611990	0.3077268
3274	-0.3788864	-0.8904536	-0.7836469	-0.7589986	0.4307274	1.1422281	A100	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.2199183
3275	0.0540848	0.6794579	-0.7836469	-0.7589986	-0.6741149	1.1422281	A155	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.2619796
3276	0.4714691	-0.8904536	0.4473277	1.3676416	-0.6741149	1.1422281	A270	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.2178404
3285	2.0111148	0.6794579	0.4434322	-0.0501185	0.4307274	1.1422281	A329	C219	1.9755430	0.5864499	0.2031375	-0.2014525	0.1203785	0.5809108	0.2319791
3293	0.0038602	-0.0817113	0.4473277	-0.0501185	-0.6741149	1.1422281	A204	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.3348188
3296	-0.3944734	2.2969425	-0.2850242	-0.7589986	0.4307274	1.1422281	A210	C301	0.3539798	2.2969425	-0.1275540	-0.2934206	-0.2808659	0.8171839	0.4013565
3307	-1.0785679	0.6794579	-0.2850242	-0.7589986	-0.6741149	1.1422281	A102	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.3492731
3312	0.9113679	2.2969425	0.0499878	-0.0501185	-0.6741149	1.1422281	A317	C301	0.3539798	2.2969425	-0.1275540	-0.2934206	-0.2808659	0.8171839	0.2827542
3314	1.1624912	-0.8904536	-0.2850242	-0.7589986	2.6404120	1.1422281	A4	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.3903394
3342	-1.5912058	-0.8904536	-0.2850242	-0.7589986	-0.6741149	1.1422281	A49	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.2549209
3344	-1.2517564	-0.0817113	-0.7758559	-0.7589986	-0.6741149	1.1422281	A51	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.2576651
3349	-0.7321909	0.6794579	-0.2850242	-0.0501185	-0.6741149	1.1422281	A154	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.3699399
3350	0.7381794	-0.0817113	0.4473277	1.3676416	-0.6741149	1.1422281	A312	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.2857084
3357	-0.9053794	-0.0817113	-0.2850242	-0.0501185	-0.6741149	1.1422281	A132	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.4478586
3361	0.4870561	0.6794579	0.4473277	-0.0501185	0.4307274	1.1422281	A277	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.2613389
3370	-1.1928723	-0.8904536	-0.9472574	-0.7589986	-0.6741149	1.1422281	A53	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1165887
3376	-1.0266114	-0.8904536	-0.6745732	-0.7589986	-0.6741149	1.1422281	A53	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1772794
3377	0.1579979	-0.8904536	-1.1420319	-0.7589986	2.6404120	1.1422281	A1	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.3618274
3382	-0.3858139	-0.0817113	-0.7836469	-0.0501185	-0.6741149	1.1422281	A120	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.3391204
3384	-0.5676619	1.1076156	-1.1926732	-1.1134387	0.4307274	1.1422281	A68	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.4789084
3395	0.4714691	-0.8904536	0.4473277	1.3676416	0.4307274	1.1422281	A307	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.3330261
3398	-0.3009516	-1.2710382	0.0499878	-0.0501185	-0.6741149	1.1422281	A159	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.2127157
3403	0.0714037	-0.0817113	-0.2850242	-0.7589986	-0.6741149	1.1422281	A156	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.3517200
3404	-0.2472631	0.6794579	0.0460923	-0.0501185	0.4307274	1.1422281	A234	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.2364583
3408	-1.0716404	-0.8904536	-0.7914378	-0.7589986	-0.6741149	1.5724304	A25	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.2219975
3417	1.5781436	0.6794579	0.4434322	-0.0501185	-0.6741149	1.5724304	A300	C219	1.9755430	0.5864499	0.2031375	-0.2014525	0.1203785	0.5809108	0.4446749
3428	0.7052736	0.6794579	0.4551187	-0.0501185	2.6404120	1.5724304	A336	C142	0.1328959	0.6627507	0.4814828	-0.0248014	2.6404120	-0.9712527	0.5307415
3430	-0.7321909	1.1076156	-1.1926732	-1.1134387	-0.6741149	1.5724304	A30	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.4304218
3431	-0.7252634	0.6794579	-0.7836469	-0.7589986	-0.6741149	1.5724304	A131	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.2789856
3434	-0.9157707	-1.2710382	-0.7836469	-0.7589986	-0.6741149	1.5724304	A25	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.2629419
3443	-0.5676619	-1.2710382	0.0499878	-0.0501185	0.4307274	1.5724304	A161	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.4022754
3453	-0.9053794	-0.0817113	-0.2850242	-0.0501185	-0.6741149	1.5724304	A205	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.5195590
3471	-0.0325094	2.2969425	-0.2850242	-0.0501185	-0.6741149	1.5724304	A283	C301	0.3539798	2.2969425	-0.1275540	-0.2934206	-0.2808659	0.8171839	0.3226262
3472	-0.3269299	-0.8904536	0.0266149	-0.0501185	-0.6741149	1.5724304	A153	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.2514670
3478	-0.5676619	-1.2710382	0.0499878	-0.0501185	-0.6741149	1.5724304	A135	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.3288678
3484	-0.3788864	0.6794579	-0.2850242	-0.0501185	0.4307274	1.5724304	A234	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.3346129
3498	0.8265055	0.6794579	0.4473277	-0.0501185	0.4307274	1.5724304	A267	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.3896141
3503	0.3138676	0.6794579	-0.7836469	-0.7589986	0.4307274	1.5724304	A173	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.4057067
3504	0.3918024	-1.2710382	0.4473277	1.3676416	-0.6741149	1.5724304	A270	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.3662493
3505	2.7385064	0.6794579	0.4434322	-0.0501185	2.6404120	1.5724304	A394	C96	2.0782294	0.7478725	0.1122044	0.7127714	2.6404120	0.5611990	0.4723402
3508	-1.2517564	-0.0817113	-0.7758559	-0.7589986	-0.6741149	1.5724304	A103	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.3293655
3510	-1.0785679	0.6794579	-1.1926732	-1.1134387	-0.6741149	1.5724304	A17	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.4167917
3518	0.2272733	2.2969425	0.0266149	-0.0501185	0.4307274	1.5724304	A332	C301	0.3539798	2.2969425	-0.1275540	-0.2934206	-0.2808659	0.8171839	0.3318362
3519	-0.1277631	-0.8904536	0.0499878	-0.0501185	-0.6741149	1.5724304	A153	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.2143770
3526	-0.0394370	2.2969425	-0.7758559	-0.7589986	-0.6741149	1.5724304	A19	C301	0.3539798	2.2969425	-0.1275540	-0.2934206	-0.2808659	0.8171839	0.4426320
3531	1.0862882	2.2969425	0.4940736	-0.0501185	2.6404120	1.5724304	A395	C96	2.0782294	0.7478725	0.1122044	0.7127714	2.6404120	0.5611990	0.7828337
3532	2.2189410	2.2969425	2.2859986	1.3676416	0.4307274	1.5724304	A396	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.9065419
3533	-1.2171187	-0.8904536	-0.7914378	-0.7589986	-0.6741149	1.5724304	A25	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1977511
3534	0.5892373	2.2969425	0.0460923	-0.0501185	-0.6741149	1.5724304	A283	C301	0.3539798	2.2969425	-0.1275540	-0.2934206	-0.2808659	0.8171839	0.3001169
3542	0.3485053	-0.8904536	-0.7836469	-0.7589986	2.6404120	1.5724304	A4	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.3796746
3547	0.5667228	2.2969425	0.4551187	-0.0501185	0.4307274	1.5724304	A332	C301	0.3539798	2.2969425	-0.1275540	-0.2934206	-0.2808659	0.8171839	0.4175930
3555	0.2792299	2.2969425	0.0266149	-0.0501185	-0.6741149	1.5724304	A283	C301	0.3539798	2.2969425	-0.1275540	-0.2934206	-0.2808659	0.8171839	0.2701194
3557	-1.0802998	-0.8904536	-0.2850242	-0.7589986	0.4307274	1.5724304	A12	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.3426043
3563	-0.3009516	-1.2710382	0.0499878	-0.0501185	-0.6741149	1.5724304	A153	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.2844161
3567	-0.5676619	-1.2710382	0.4473277	-0.0501185	-0.6741149	1.5724304	A135	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.3948952
3572	0.4783966	-1.2710382	0.4473277	1.3676416	-0.6741149	1.5724304	A270	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.3518170
3575	1.3356797	0.6794579	0.0421969	-0.0501185	-0.6741149	1.5724304	A240	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.3910583
3577	0.2168820	0.6794579	0.0499878	-0.0501185	-0.6741149	1.5724304	A240	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.2695569
3580	-0.0671471	0.6794579	0.0460923	-0.0501185	-0.6741149	1.5724304	A240	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.3162459
3583	-1.0785679	-0.8904536	-0.7758559	-0.7589986	-0.6741149	1.5724304	A25	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.2234399
3587	1.5781436	2.2969425	0.4434322	1.3676416	0.4307274	1.5724304	A396	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.4926480
3588	-1.0266114	-0.8904536	-0.6745732	-0.7589986	-0.6741149	1.5724304	A46	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.2489798
3590	-0.5070459	-0.8904536	-0.2850242	-0.7589986	2.6404120	1.5724304	A2	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.4313385
3591	1.5106000	2.2969425	0.4473277	1.3676416	0.4307274	1.5724304	A396	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.4820400
3596	-0.0498283	-0.8904536	-0.7836469	-0.7589986	0.4307274	1.5724304	A100	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.3464617
3597	0.9096360	2.2969425	0.0499878	-0.0501185	-0.6741149	1.5724304	A317	C301	0.3539798	2.2969425	-0.1275540	-0.2934206	-0.2808659	0.8171839	0.3541659
3598	-1.4180174	-0.8904536	-0.7914378	-0.7589986	-0.6741149	1.5724304	A25	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.2133543
3611	-0.3858139	1.1076156	-0.7758559	-0.7589986	-0.6741149	1.5724304	A134	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.3330217
3613	1.0932158	0.6794579	0.4434322	1.3676416	0.4307274	1.5724304	A362	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.3219675
3616	-0.8118576	-0.8904536	-0.7836469	-0.7589986	-0.6741149	1.5724304	A46	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.2457954
3619	-0.3944734	-0.0817113	0.0266149	-0.7589986	-0.6741149	1.5724304	A103	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.4262745
3623	0.6879547	2.2969425	-0.2850242	-0.0501185	2.6404120	1.5724304	A395	C301	0.3539798	2.2969425	-0.1275540	-0.2934206	-0.2808659	0.8171839	0.7352120
3631	0.7745490	2.2969425	0.4940736	-0.0501185	0.4307274	1.5724304	A332	C301	0.3539798	2.2969425	-0.1275540	-0.2934206	-0.2808659	0.8171839	0.4587231
3633	0.0991138	0.6794579	0.4551187	-0.0501185	0.4307274	1.5724304	A267	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.3186003
3639	-0.0394370	0.6794579	0.0499878	-0.0501185	-0.6741149	1.5724304	A240	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.3122768
3644	1.0412592	-0.0817113	-0.2850242	-0.0501185	0.4307274	1.5724304	A252	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.4316320
3648	-0.4377705	2.2969425	-0.7914378	-0.7589986	-0.6741149	1.5724304	A19	C301	0.3539798	2.2969425	-0.1275540	-0.2934206	-0.2808659	0.8171839	0.5116179
3650	-0.2212849	2.2969425	-1.1926732	-1.1134387	0.4307274	1.5724304	A210	C301	0.3539798	2.2969425	-0.1275540	-0.2934206	-0.2808659	0.8171839	0.6545403
3651	-0.0480964	-0.0817113	0.4473277	-0.0501185	-0.6741149	1.5724304	A205	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.4019170
3655	-0.8534229	-0.8904536	-0.2850242	-0.7589986	2.6404120	1.5724304	A2	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.4890680
3662	-0.8205171	0.6794579	-1.1926732	-1.1134387	-0.6741149	1.5724304	A67	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.3737832
3671	0.7087373	2.2969425	0.4940736	-0.0501185	0.4307274	1.5724304	A332	C301	0.3539798	2.2969425	-0.1275540	-0.2934206	-0.2808659	0.8171839	0.4477545
3679	0.1250921	0.6794579	0.4473277	-0.0501185	-0.6741149	1.5724304	A240	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.3510786
3681	-1.0785679	0.6794579	-0.7758559	-0.7589986	-0.6741149	1.5724304	A102	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.3391682
3689	1.7513320	0.6794579	0.4434322	-0.0501185	-0.6741149	1.5724304	A300	C219	1.9755430	0.5864499	0.2031375	-0.2014525	0.1203785	0.5809108	0.4158101
3697	0.9996940	1.1076156	0.4473277	1.3676416	-0.6741149	1.5724304	A363	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.3440322
3698	-0.3858139	-0.8904536	0.0460923	-0.0501185	0.4307274	1.5724304	A200	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.3368919
3708	-1.4249449	-0.8904536	-0.7758559	-0.7589986	-0.6741149	1.5724304	A25	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.2171059
3721	0.1753168	-0.8904536	-0.2850242	-0.7589986	-0.6741149	1.5724304	A96	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.3842156
3724	1.2317666	0.6794579	0.4434322	1.3676416	0.4307274	1.5724304	A362	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.2988757
3725	-0.9140388	0.6794579	-1.1926732	-1.1134387	-0.6741149	1.5724304	A67	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.3893702
3730	1.1278535	0.6794579	-0.2850242	-0.0501185	-0.6741149	1.5724304	A251	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.3716236
3732	-0.5849807	2.2969425	-0.7914378	-0.7589986	0.4307274	1.5724304	A210	C301	0.3539798	2.2969425	-0.1275540	-0.2934206	-0.2808659	0.8171839	0.5892104
3736	-0.7408504	-0.0817113	-0.7758559	-0.7589986	0.4307274	1.5724304	A149	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.4357887
3737	-0.2212849	-0.8904536	0.0499878	-0.0501185	0.4307274	1.5724304	A200	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.3649627
3738	-0.5607343	-0.0817113	0.0266149	-0.7589986	0.4307274	1.5724304	A149	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.4244049
3739	-0.1294950	-0.8904536	0.0499878	-0.0501185	-0.6741149	1.5724304	A153	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.2146656
3745	-0.0480964	2.2969425	-0.7758559	-0.7589986	-0.6741149	0.6851382	A19	C301	0.3539798	2.2969425	-0.1275540	-0.2934206	-0.2808659	0.8171839	0.3402084
3747	-0.3788864	-0.8904536	0.4434322	-0.7589986	-0.6741149	0.6851382	A127	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.2678298
3754	-1.4526551	-0.8904536	-0.2850242	-0.7589986	-0.6741149	0.6851382	A89	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.2135717
3757	0.0436935	0.6794579	0.0499878	-0.0501185	-0.6741149	0.6851382	A216	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.1505396
3759	-0.2160892	-0.8904536	0.0499878	-0.0501185	-0.6741149	0.6851382	A157	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.0812160
3760	-1.0266114	-0.8904536	-0.6745732	-0.7589986	-0.6741149	0.6851382	A77	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1518846
3764	-0.9071113	-0.8904536	-0.7758559	-0.7589986	-0.6741149	0.6851382	A77	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1150875
3766	0.2203458	-0.8904536	0.4473277	1.3676416	-0.6741149	0.6851382	A264	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.1835126
3776	0.8265055	0.6794579	0.4940736	1.3676416	0.4307274	0.6851382	A348	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.2310513
3778	0.3069400	2.2969425	0.0499878	-0.0501185	-0.6741149	0.6851382	A279	C301	0.3539798	2.2969425	-0.1275540	-0.2934206	-0.2808659	0.8171839	0.1655297
3779	-0.2645820	-0.8904536	0.4940736	-0.0501185	0.4307274	0.6851382	A213	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.2838787
3782	-0.2160892	-0.8904536	0.0499878	-0.0501185	-0.6741149	0.6851382	A157	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.0812160
3788	1.0066215	0.6794579	0.4434322	1.3676416	0.4307274	0.6851382	A359	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.1925917
3791	1.5192595	0.6794579	2.2859986	2.7854017	-0.6741149	0.6851382	A417	C55	1.4810668	0.0181922	2.3175726	2.6287019	0.1225346	-0.2170130	0.4310888
3792	0.4870561	0.6794579	-0.2850242	-0.7589986	-0.6741149	0.6851382	A195	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.1836006
3793	-0.3078791	-0.8904536	0.0499878	-0.0501185	-0.6741149	0.6851382	A157	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.0965143
3795	1.3529985	2.2969425	0.4473277	1.3676416	2.6404120	0.6851382	A424	C96	2.0782294	0.7478725	0.1122044	0.7127714	2.6404120	0.5611990	0.5647056
3811	-0.8984519	-0.0817113	-0.2850242	-0.0501185	0.4307274	0.6851382	A149	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.3067138
3817	-1.0716404	-0.8904536	-0.7914378	-0.7589986	-0.6741149	0.6851382	A62	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1320396
3819	-1.5912058	-0.8904536	-0.7914378	-0.7589986	-0.6741149	0.6851382	A54	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1522612
3824	-0.1260312	0.6794579	0.4940736	-0.0501185	0.4307274	0.6851382	A266	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.2147349
3826	1.2594767	-0.8904536	2.2859986	2.7854017	-0.6741149	0.6851382	A404	C55	1.4810668	0.0181922	2.3175726	2.6287019	0.1225346	-0.2170130	0.5028851
3832	0.5840416	0.6794579	0.4940736	-0.0501185	0.4307274	0.6851382	A277	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.2091124
3838	0.3623603	0.6794579	0.4940736	-0.0501185	0.4307274	0.6851382	A266	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.1721656
3839	0.9113679	0.6794579	0.4473277	1.3676416	-0.6741149	0.6851382	A327	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.2470019
3841	-0.1537414	0.6794579	0.0266149	-0.0501185	-0.6741149	0.6851382	A216	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.1795500
3850	0.4870561	2.2969425	0.0577788	1.3676416	0.4307274	0.6851382	A392	C301	0.3539798	2.2969425	-0.1275540	-0.2934206	-0.2808659	0.8171839	0.4705184
3852	0.9996940	2.2969425	0.4473277	1.3676416	-0.6741149	0.6851382	A388	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.3984452
3860	-0.0325094	0.6794579	0.0266149	-0.0501185	-0.6741149	0.6851382	A216	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.1593446
3867	-0.9919737	-0.8904536	-0.7758559	-0.7589986	-0.6741149	0.6851382	A77	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1292312
3868	-0.8187852	0.6794579	0.0460923	-0.0501185	0.4307274	0.6851382	A233	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.2555303
3870	0.8143823	-0.8904536	-0.7836469	-0.7589986	2.6404120	0.6851382	A4	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.3094387
3871	0.3848748	-0.8904536	0.4473277	1.3676416	-0.6741149	0.6851382	A264	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.1560911
3874	1.2560130	-0.8904536	2.2859986	2.7854017	-0.6741149	0.6851382	A404	C55	1.4810668	0.0181922	2.3175726	2.6287019	0.1225346	-0.2170130	0.5034623
3875	0.1406791	0.6794579	0.0577788	1.3676416	0.4307274	0.6851382	A341	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.3338607
3880	0.7225924	0.6794579	2.5976378	-0.0501185	0.4307274	0.6851382	A346	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.5827983
3881	-0.0480964	0.6794579	0.0499878	-0.0501185	0.4307274	0.6851382	A247	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.1277315
3886	-1.0785679	0.6794579	-0.7758559	-0.7589986	-0.6741149	0.6851382	A102	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.1912861
3894	1.4309333	-0.8904536	2.2859986	2.7854017	-0.6741149	0.6851382	A404	C55	1.4810668	0.0181922	2.3175726	2.6287019	0.1225346	-0.2170130	0.4743090
3895	0.4714691	2.2969425	0.4473277	-0.0501185	-0.6741149	0.6851382	A279	C301	0.3539798	2.2969425	-0.1275540	-0.2934206	-0.2808659	0.8171839	0.2434946
3902	-0.7339228	-0.8904536	-0.2850242	-0.7589986	-0.6741149	0.6851382	A108	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1680280
3913	-1.2448289	-0.8904536	-0.7914378	-0.7589986	0.4307274	0.6851382	A76	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.2580452
3915	0.6931504	0.6794579	0.0577788	1.3676416	2.6404120	0.6851382	A399	C96	2.0782294	0.7478725	0.1122044	0.7127714	2.6404120	0.5611990	0.3811214
3921	0.5494039	-0.8904536	2.5976378	-0.0501185	0.4307274	0.6851382	A346	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.7508350
3923	0.0869906	-0.8904536	-0.7836469	-0.7589986	0.4307274	0.6851382	A122	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.2213829
3930	-1.4180174	-0.0817113	-0.2850242	-0.7589986	-0.6741149	0.6851382	A132	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.3425891
3943	-0.4758720	-0.8904536	0.0499878	-0.0501185	-0.6741149	0.6851382	A157	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.1245131
3947	-0.1727921	-0.0817113	-0.6356183	-0.7589986	2.6404120	0.6851382	A11	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.2477972
3948	-1.4249449	-0.8904536	-0.7758559	-0.7589986	-0.6741149	0.6851382	A54	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1271480
3957	0.4524184	2.2969425	0.0266149	-0.0501185	0.4307274	0.6851382	A324	C301	0.3539798	2.2969425	-0.1275540	-0.2934206	-0.2808659	0.8171839	0.2232581
3958	2.2033540	2.2969425	2.2859986	2.7854017	0.4307274	0.6851382	A431	C55	1.4810668	0.0181922	2.3175726	2.6287019	0.1225346	-0.2170130	0.7332759
3960	-0.1260312	-0.8904536	0.4940736	-0.0501185	0.4307274	0.6851382	A213	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.3069705
3961	0.3225270	-0.8904536	0.4473277	1.3676416	-0.6741149	0.6851382	A264	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.1664824
3967	-1.0266114	-0.8904536	0.0460923	-0.0501185	0.4307274	0.6851382	A176	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.2668049
3969	-0.8187852	-0.8904536	0.0460923	-0.0501185	0.4307274	0.6851382	A176	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.2321672
3970	1.2317666	0.6794579	0.4434322	1.3676416	0.4307274	0.6851382	A359	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.1550675
3971	0.2186139	2.2969425	-0.7758559	-0.7589986	-0.6741149	0.6851382	A19	C301	0.3539798	2.2969425	-0.1275540	-0.2934206	-0.2808659	0.8171839	0.2957567
3974	-0.5676619	-0.8904536	0.0499878	-0.0501185	-0.6741149	0.6851382	A157	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.1398114
3994	1.1798100	0.6794579	0.4434322	1.3676416	0.4307274	0.6851382	A359	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.1637269
4003	0.5320851	0.6794579	0.4940736	1.3676416	0.4307274	0.6851382	A348	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.2801213
4017	-0.3858139	0.6794579	-0.2850242	-0.7589986	-0.6741149	0.0398347	A174	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.2955309
4021	-0.5590024	0.6794579	0.0460923	-0.0501185	-0.6741149	0.0398347	A225	C306	-0.7716661	0.5467115	0.2755179	-0.2228202	-0.1702066	-0.7871317	0.3464020
4024	-1.0872273	-0.8904536	0.0499878	-0.7589986	0.4307274	0.0398347	A148	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.3314474
4032	-0.2056979	0.6794579	0.0266149	-0.0501185	-0.6741149	0.0398347	A225	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.2873031
4035	-0.5676619	0.6794579	0.0499878	-0.7589986	0.4307274	0.0398347	A194	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.3927977
4041	-1.7713219	-1.2710382	-0.7758559	-0.7589986	-0.6741149	0.0398347	A37	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.3060957
4043	0.5823097	0.6794579	0.4473277	1.3676416	-0.6741149	0.0398347	A327	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.4093955
4048	-0.5070459	0.6794579	0.0460923	-0.0501185	0.4307274	0.0398347	A254	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.3012617
4050	0.6602445	2.2969425	0.4434322	-0.0501185	0.4307274	0.0398347	A334	C301	0.3539798	2.2969425	-0.1275540	-0.2934206	-0.2808659	0.8171839	0.4349159
4053	0.7364475	0.6794579	0.4473277	1.3676416	-0.6741149	0.0398347	A327	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.3837059
4054	0.6533170	0.6794579	0.4473277	-0.0501185	0.4307274	0.0398347	A273	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.3105553
4057	0.5632590	2.2969425	0.0499878	-0.0501185	-0.6741149	0.0398347	A279	C301	0.3539798	2.2969425	-0.1275540	-0.2934206	-0.2808659	0.8171839	0.3001202
4064	-0.0480964	2.2969425	0.0499878	-0.7589986	0.4307274	0.0398347	A334	C301	0.3539798	2.2969425	-0.1275540	-0.2934206	-0.2808659	0.8171839	0.4223564
4073	1.7755784	0.6794579	2.2859986	2.7854017	-0.6741149	0.0398347	A417	C55	1.4810668	0.0181922	2.3175726	2.6287019	0.1225346	-0.2170130	0.3662581
4075	-0.0480964	0.6794579	0.0499878	-0.0501185	0.4307274	0.0398347	A273	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.2254194
4086	-1.6102566	-0.8904536	-0.2850242	-0.7589986	0.4307274	0.0398347	A139	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.3627836
4096	-1.1582346	-0.8904536	-0.7914378	-0.7589986	0.4307274	0.0398347	A86	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.3176839
4110	-1.4526551	-0.8904536	-0.2850242	-0.7589986	-0.6741149	0.0398347	A81	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.2785272
4119	-0.6300097	-0.8904536	0.0499878	-0.0501185	-0.6741149	0.0398347	A171	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.2083335
4124	-0.5676619	0.6794579	0.0499878	-0.7589986	-0.6741149	0.0398347	A174	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.3437214
4126	3.6893113	2.2969425	1.2264256	-0.0501185	2.6404120	0.0398347	A434	C96	2.0782294	0.7478725	0.1122044	0.7127714	2.6404120	0.5611990	0.9264379
4129	0.6446576	-0.8904536	2.2859986	1.3676416	-0.6741149	0.0398347	A313	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.4718131
4134	-0.5520749	0.6794579	0.0266149	-0.0501185	-0.6741149	0.0398347	A225	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.3450326
4145	-0.6923576	-0.0817113	-0.2850242	-0.7589986	2.6404120	0.0398347	A235	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.3832033
4146	-0.2922922	0.6794579	0.0266149	-0.0501185	0.4307274	0.0398347	A254	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.2622232
4149	-0.7252634	0.6794579	-0.2850242	-0.0501185	0.4307274	0.0398347	A254	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.3421483
4155	-1.2448289	-0.8904536	-0.7914378	-0.7589986	-0.6741149	0.0398347	A65	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.1899704
4157	0.2186139	0.6794579	0.0499878	-0.0501185	-0.6741149	0.0398347	A225	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.2204799
4160	1.6837885	2.2969425	2.2859986	1.3676416	-0.6741149	0.0398347	A431	C55	1.4810668	0.0181922	2.3175726	2.6287019	0.1225346	-0.2170130	0.8046006
4161	1.7149625	0.6794579	-0.5577085	-0.7589986	0.4307274	0.0398347	A302	C219	1.9755430	0.5864499	0.2031375	-0.2014525	0.1203785	0.5809108	0.4205676
4162	-1.4526551	-1.2710382	-0.7836469	-0.7589986	-0.6741149	0.0398347	A37	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.2516861
4165	0.3918024	-0.8904536	0.4473277	1.3676416	-0.6741149	0.0398347	A278	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.2075104
4171	0.2272733	2.2969425	0.0266149	-0.0501185	0.4307274	0.0398347	A334	C301	0.3539798	2.2969425	-0.1275540	-0.2934206	-0.2808659	0.8171839	0.3355200
4179	-0.6282778	0.6794579	0.0460923	-0.0501185	0.4307274	0.0398347	A254	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.3214671
4180	2.2033540	2.2969425	2.2859986	2.7854017	-0.6741149	0.0398347	A431	C55	1.4810668	0.0181922	2.3175726	2.6287019	0.1225346	-0.2170130	0.7071348
4197	0.4004618	2.2969425	0.4434322	-0.0501185	0.4307274	0.0398347	A334	C301	0.3539798	2.2969425	-0.1275540	-0.2934206	-0.2808659	0.8171839	0.3916188
4201	1.2594767	-0.8904536	2.2859986	2.7854017	-0.6741149	0.0398347	A404	C55	1.4810668	0.0181922	2.3175726	2.6287019	0.1225346	-0.2170130	0.3953345
4208	2.2033540	2.2969425	2.2859986	2.7854017	0.4307274	0.0398347	A431	C55	1.4810668	0.0181922	2.3175726	2.6287019	0.1225346	-0.2170130	0.6257253
4210	1.3339478	-0.8904536	-0.5577085	-0.7589986	2.6404120	0.0398347	A311	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.4358161
4211	-1.4180174	-0.0817113	-0.7914378	-0.7589986	-0.6741149	0.0398347	A94	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.3209010
4212	-0.3009516	0.6794579	0.0499878	-0.7589986	-0.6741149	0.0398347	A174	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.3655100
4215	1.6924480	0.6794579	2.5976378	1.3676416	2.6404120	0.0398347	A409	C96	2.0782294	0.7478725	0.1122044	0.7127714	2.6404120	0.5611990	0.6859773
4216	-0.5676619	-0.8904536	0.0499878	-0.0501185	-0.6741149	0.0398347	A171	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.1979422
4222	2.4700643	2.2969425	2.2859986	2.7854017	-0.6741149	0.0398347	A431	C55	1.4810668	0.0181922	2.3175726	2.6287019	0.1225346	-0.2170130	0.7515865
4225	0.2168820	-0.8904536	0.4473277	1.3676416	-0.6741149	0.0398347	A278	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.2366638
4226	-0.3459806	-0.0817113	-0.2850242	-0.0501185	2.6404120	0.0398347	A235	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.3275465
4234	1.6214407	0.6794579	2.2859986	2.7854017	-0.6741149	0.0398347	A417	C55	1.4810668	0.0181922	2.3175726	2.6287019	0.1225346	-0.2170130	0.3405684
4236	0.3848748	-0.8904536	0.4473277	1.3676416	0.4307274	0.0398347	A315	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.3238507
4250	-1.3383506	-0.0817113	-0.7758559	-0.7589986	-0.6741149	0.3490426	A94	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.3035220
4253	-0.9850461	0.6794579	-0.7836469	-0.7589986	0.4307274	0.3490426	A194	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.3704201
4260	1.3339478	-0.8904536	-0.5577085	-0.7589986	2.6404120	0.3490426	A311	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.3842814
4264	-0.3511762	0.6794579	0.4940736	-0.0501185	0.4307274	0.3490426	A266	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.2984124
4272	0.7364475	0.6794579	1.1952617	1.3676416	-0.6741149	0.3490426	A327	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.4568269
4274	-0.4377705	0.6794579	0.4940736	-0.0501185	-0.6741149	0.3490426	A225	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.3523570
4278	-1.1599665	-0.8904536	-0.2850242	-0.7589986	-0.6741149	0.3490426	A89	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.2553580
4292	2.3315135	0.6794579	-0.1915325	-0.0501185	0.4307274	0.3490426	A302	C219	1.9755430	0.5864499	0.2031375	-0.2014525	0.1203785	0.5809108	0.2561999
4296	-0.5070459	0.6794579	0.0460923	-0.0501185	0.4307274	0.3490426	A233	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.2497271
4304	-0.2056979	0.6794579	0.0266149	-0.0501185	-0.6741149	0.3490426	A225	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.2357684
4306	-0.3788864	0.6794579	0.0266149	-0.0501185	-0.6741149	0.3490426	A225	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.2646332
4315	-1.4180174	0.6794579	-0.2850242	-0.7589986	-0.6741149	0.3490426	A174	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.3780773
4324	0.9113679	0.6794579	1.1952617	1.3676416	-0.6741149	0.3490426	A327	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.4276735
4327	-0.3806183	0.6794579	-0.2850242	-0.0501185	0.4307274	0.3490426	A233	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.2331728
4330	-1.2448289	-0.8904536	-0.2850242	-0.7589986	-0.6741149	0.3490426	A89	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.2435931
4331	1.4240058	-0.8904536	2.2859986	2.7854017	0.4307274	0.3490426	A411	C55	1.4810668	0.0181922	2.3175726	2.6287019	0.1225346	-0.2170130	0.3380382
4348	-1.2448289	-0.8904536	-0.7914378	-0.7589986	-0.6741149	0.3490426	A65	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.1591908
4349	0.5632590	-0.8904536	1.1952617	1.3676416	-0.6741149	0.3490426	A313	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.2520553
4351	0.5823097	0.6794579	1.1952617	1.3676416	-0.6741149	0.3490426	A327	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.4825165
4352	1.6907161	-0.8904536	2.2859986	2.7854017	-0.6741149	0.3490426	A404	C55	1.4810668	0.0181922	2.3175726	2.6287019	0.1225346	-0.2170130	0.4448790
4363	-0.4464299	0.6794579	0.0460923	-0.0501185	0.4307274	0.3490426	A233	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.2396244
4365	-1.7643943	-0.8904536	-0.7914378	-0.7589986	-0.6741149	0.3490426	A54	C512	-1.2707584	-1.0397430	-0.9098567	-0.8315183	-0.5949957	0.8589108	0.2371419
4375	1.0776288	2.2969425	1.1952617	1.3676416	-0.6741149	0.3490426	A388	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.5661277
4379	0.9044403	2.2969425	2.2859986	-0.0501185	-0.6741149	0.3490426	A279	C301	0.3539798	2.2969425	-0.1275540	-0.2934206	-0.2808659	0.8171839	0.6781176
4392	-0.2749733	0.6794579	0.0460923	-0.0501185	0.4307274	0.3490426	A233	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.2110483
4396	-0.9919737	-0.8904536	-0.7758559	-0.7589986	-0.6741149	0.3490426	A92	C471	-0.5129045	-0.9728948	-0.8664462	-0.7547916	-0.6741149	0.5660586	0.1455540
4404	-1.4249449	-1.2710382	-0.2850242	-0.0501185	-0.6741149	0.3490426	A115	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.3862978
4406	0.5667228	0.6794579	0.4473277	-0.0501185	0.4307274	0.3490426	A277	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.2445883
4409	0.6602445	0.6794579	0.4434322	1.3676416	0.4307274	0.3490426	A348	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.3063371
4419	-1.2985173	-0.8904536	-0.2850242	-0.7589986	0.4307274	0.3490426	A76	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.2592924
4430	-0.3858139	2.2969425	-0.7758559	-0.7589986	-0.6741149	0.3490426	A19	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.4317718
4436	-0.3788864	0.6794579	0.0266149	-0.0501185	-0.6741149	0.3490426	A225	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.2646332
4441	1.3443391	2.2969425	1.1952617	1.3676416	-0.6741149	0.3490426	A388	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.5290786
4446	0.8143823	-0.8904536	-0.5577085	-0.7589986	0.4307274	0.3490426	A207	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.3331589
4448	-0.2819008	0.6794579	1.2342166	-0.0501185	-0.6741149	0.3490426	A289	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.4497359
4449	1.4309333	-0.8904536	2.2859986	2.7854017	-0.6741149	0.3490426	A404	C55	1.4810668	0.0181922	2.3175726	2.6287019	0.1225346	-0.2170130	0.4182930
4450	-0.2836327	2.2969425	-0.7758559	-0.7589986	-0.6741149	0.3490426	A19	C301	0.3539798	2.2969425	-0.1275540	-0.2934206	-0.2808659	0.8171839	0.4354804
4458	1.5261870	0.6794579	2.2859986	1.3676416	0.4307274	0.3490426	A402	C55	1.4810668	0.0181922	2.3175726	2.6287019	0.1225346	-0.2170130	0.4788781
4459	-0.7252634	0.6794579	-0.2850242	-0.0501185	-0.6741149	0.3490426	A184	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.3401627
4463	0.2186139	0.6794579	0.4473277	-0.0501185	-0.6741149	0.3490426	A225	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.2351686
4465	-0.3858139	0.6794579	0.0460923	-0.0501185	-0.6741149	0.3490426	A225	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.2690340
4471	0.3069400	-0.8904536	1.1952617	1.3676416	-0.6741149	0.3490426	A313	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.2947752
4477	-1.2985173	-0.0817113	-0.2850242	-0.7589986	0.4307274	0.3490426	A149	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.3757473
4478	2.1946946	0.6794579	6.5710368	1.3676416	0.4307274	0.3490426	A438	B12	5.5095223	0.6794579	3.0650965	4.2031619	2.6404120	0.4969247	2.0023092
4483	-0.8828649	0.6794579	-0.2850242	-0.7589986	-0.6741149	0.3490426	A174	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.2888852
4486	-0.4135241	-0.8904536	0.4473277	-0.0501185	0.4307274	0.3490426	A213	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.2794646
4491	1.0066215	0.6794579	0.4434322	1.3676416	2.6404120	-0.2290417	A399	C96	2.0782294	0.7478725	0.1122044	0.7127714	2.6404120	0.5611990	0.4860602
4493	-0.8274446	-0.8904536	-0.7758559	-0.7589986	-0.6741149	-0.2290417	A93	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.1914855
4513	-0.8897925	-0.8904536	-0.7758559	-0.7589986	-0.6741149	-0.2290417	A93	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.1810942
4523	-0.7321909	-0.8904536	0.4473277	-0.0501185	-0.6741149	-0.2290417	A198	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.3362038
4525	-0.7166040	-0.0817113	-0.7758559	-0.7589986	-0.6741149	-0.2290417	A113	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.3080277
4529	-1.4249449	-0.0817113	-0.7758559	-0.7589986	-0.6741149	-0.2290417	A116	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.2746459
4531	0.4801285	0.6794579	0.4473277	-0.0501185	-0.6741149	-0.2290417	A260	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.3120126
4537	0.0384979	-0.8904536	2.2859986	-0.0501185	-0.6741149	-0.2290417	A258	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.5390083
4542	0.2982806	0.6794579	0.4473277	-0.0501185	-0.6741149	-0.2290417	A260	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.3182382
4543	-0.6750387	0.6794579	0.0460923	-0.0501185	-0.6741149	-0.2290417	A232	C306	-0.7716661	0.5467115	0.2755179	-0.2228202	-0.1702066	-0.7871317	0.2822499
4544	-1.2448289	-0.8904536	-0.2850242	-0.7589986	-0.6741149	-0.2290417	A81	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.1990767
4549	0.5649909	-0.8904536	1.1952617	1.3676416	0.4307274	-0.2290417	A352	C130	0.2826529	-0.0067137	1.6381330	0.9923522	0.2097590	-0.6177263	0.4323153
4555	-1.3331550	-0.8904536	-0.2850242	-0.7589986	0.4307274	-0.2290417	A148	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.3477180
4558	-0.2056979	0.6794579	0.0266149	-0.0501185	-0.6741149	-0.2290417	A232	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.3321158
4563	-0.5520749	0.6794579	0.0266149	-0.0501185	-0.6741149	-0.2290417	A232	C306	-0.7716661	0.5467115	0.2755179	-0.2228202	-0.1702066	-0.7871317	0.3059901
4572	0.1389472	-0.8904536	0.4473277	-0.0501185	2.6404120	-0.2290417	A249	C142	0.1328959	0.6627507	0.4814828	-0.0248014	2.6404120	-0.9712527	0.3934898
4574	-1.0716404	0.6794579	-0.2850242	-0.0501185	0.4307274	-0.2290417	A245	C306	-0.7716661	0.5467115	0.2755179	-0.2228202	-0.1702066	-0.7871317	0.3874981
4575	-0.0411688	-0.8904536	0.4473277	-0.0501185	-0.6741149	-0.2290417	A198	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.2210335
4577	-1.1253288	-0.8904536	-0.6356183	-1.1134387	2.6404120	-0.2290417	A13	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.5964569
4579	-1.6102566	-0.8904536	-0.2850242	-0.7589986	0.4307274	-0.2290417	A139	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.3939016
4587	-0.9504084	0.6794579	0.0460923	-0.0501185	-0.6741149	-0.2290417	A232	C306	-0.7716661	0.5467115	0.2755179	-0.2228202	-0.1702066	-0.7871317	0.2959357
4594	-1.7643943	-0.8904536	-0.7914378	-0.7589986	-0.6741149	-0.2290417	A52	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.2317519
4597	-1.4180174	0.6794579	-0.2850242	-0.7589986	-0.6741149	-0.2290417	A129	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.4568689
4606	1.1642231	0.6794579	1.1952617	1.3676416	0.4307274	-0.2290417	A378	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.4439930
4609	-0.5018502	0.6794579	0.0460923	-0.0501185	-0.6741149	-0.2290417	A232	C306	-0.7716661	0.5467115	0.2755179	-0.2228202	-0.1702066	-0.7871317	0.3111146
4610	0.1337515	-0.8904536	1.1952617	1.3676416	0.4307274	-0.2290417	A351	C130	0.2826529	-0.0067137	1.6381330	0.9923522	0.2097590	-0.6177263	0.4100758
4615	-0.1346906	-0.0817113	0.4473277	-0.0501185	0.4307274	-0.2290417	A242	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.4194690
4616	-0.0325094	0.6794579	0.4473277	-0.0501185	0.4307274	-0.2290417	A287	C297	0.2458726	0.5046167	-0.1059150	-0.1622064	0.4307274	0.6555503	0.3338576
4618	-1.0872273	-0.8904536	-0.7758559	-0.7589986	-0.6741149	-0.2290417	A93	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.1481884
4634	-0.7321909	0.6794579	-0.2850242	-0.7589986	-0.6741149	-0.2290417	A174	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.3601203
4637	1.9591582	2.2969425	1.2264256	-0.0501185	-0.6741149	-0.2290417	A393	C219	1.9755430	0.5864499	0.2031375	-0.2014525	0.1203785	0.5809108	0.7509909
4642	1.5348464	-0.8904536	2.2859986	2.7854017	0.4307274	-0.2290417	A416	C55	1.4810668	0.0181922	2.3175726	2.6287019	0.1225346	-0.2170130	0.2451534
4646	2.9619196	2.2969425	1.2264256	-0.0501185	0.4307274	-0.2290417	A393	C219	1.9755430	0.5864499	0.2031375	-0.2014525	0.1203785	0.5809108	0.8319655
4656	1.0776288	-0.8904536	1.1952617	1.3676416	2.6404120	-0.2290417	A401	C228	0.8544662	-0.8230415	0.4195786	1.3676416	-0.4672508	0.5202082	0.8205284
4659	-0.6542561	-0.0817113	-0.7758559	-0.7589986	0.4307274	-0.2290417	A164	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.3980222
4660	-1.9375828	-0.8904536	-0.2850242	-0.7589986	-0.6741149	-0.2290417	A81	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.3145357
4665	-1.2448289	-0.8904536	-0.7914378	-0.7589986	-0.6741149	-0.2290417	A66	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.1451577
4668	-0.8828649	0.6794579	0.4940736	-0.7589986	-0.6741149	-0.2290417	A182	C306	-0.7716661	0.5467115	0.2755179	-0.2228202	-0.1702066	-0.7871317	0.3434463
4669	1.0862882	-0.8904536	2.2859986	2.7854017	0.4307274	-0.2290417	A416	C55	1.4810668	0.0181922	2.3175726	2.6287019	0.1225346	-0.2170130	0.3019866
4677	-0.2420675	-0.8904536	-0.2850242	-0.7589986	2.6404120	-0.2290417	A13	C360	0.2356188	-0.4603485	-0.3744382	-0.4107768	2.6404120	0.5948051	0.3615457
4678	0.5476720	0.6794579	1.2342166	-0.0501185	2.6404120	-0.2290417	A387	C142	0.1328959	0.6627507	0.4814828	-0.0248014	2.6404120	-0.9712527	0.3252909
4681	-1.4249449	-1.2710382	-0.2850242	-0.0501185	-0.6741149	-0.2290417	A124	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.4095995
4684	-0.2056979	-0.8904536	-0.7836469	-0.0501185	-0.6741149	-0.2290417	A133	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.3213667
4686	3.6893113	2.2969425	1.2264256	-0.0501185	2.6404120	-0.2290417	A434	C96	2.0782294	0.7478725	0.1122044	0.7127714	2.6404120	0.5611990	0.9712506
4688	-1.1495752	-0.8904536	-0.7758559	-0.7589986	-0.6741149	-0.2290417	A93	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.1377971
4689	-0.4724082	0.6794579	-0.2850242	-0.7589986	-0.6741149	-0.2290417	A174	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.3259113
4707	-0.5676619	-0.8904536	0.4473277	-0.0501185	-0.6741149	-0.8071260	A186	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.4051297
4711	-0.6906257	-0.8904536	-0.5577085	-0.7589986	-0.6741149	-0.8071260	A74	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.1665305
4716	-0.3078791	-0.0817113	0.4473277	-0.0501185	0.4307274	-0.8071260	A242	C306	-0.7716661	0.5467115	0.2755179	-0.2228202	-0.1702066	-0.7871317	0.3429416
4717	0.0384979	-0.8904536	2.2859986	-0.0501185	-0.6741149	-0.8071260	A258	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.6353557
4726	0.0384979	-0.0817113	2.2859986	-0.0501185	-0.6741149	-0.8071260	A319	C130	0.2826529	-0.0067137	1.6381330	0.9923522	0.2097590	-0.6177263	0.5137938
4728	-0.9053794	0.6794579	-0.7758559	-0.7589986	-0.6741149	-0.8071260	A150	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.3485969
4732	0.6498532	-0.0817113	1.1952617	1.3676416	0.4307274	-0.8071260	A364	C130	0.2826529	-0.0067137	1.6381330	0.9923522	0.2097590	-0.6177263	0.2784545
4734	-0.3702270	-0.8904536	0.4473277	-0.0501185	-0.6741149	-0.8071260	A198	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.3722239
4736	-1.0785679	-0.8904536	-0.2850242	-0.0501185	-0.6741149	-0.8071260	A124	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.2643934
4748	-1.5046116	-0.8904536	-0.5577085	-0.7589986	-0.6741149	-0.8071260	A41	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.1380996
4749	0.3138676	0.6794579	0.4434322	1.3676416	0.4307274	-0.8071260	A372	C130	0.2826529	-0.0067137	1.6381330	0.9923522	0.2097590	-0.6177263	0.4496241
4752	-0.7252634	0.6794579	0.0266149	-0.0501185	-0.6741149	-0.8071260	A224	C306	-0.7716661	0.5467115	0.2755179	-0.2228202	-0.1702066	-0.7871317	0.1874427
4753	0.6602445	0.6794579	0.4434322	1.3676416	0.4307274	-0.8071260	A376	C147	1.3221312	0.9897072	0.3646278	1.3676416	-0.0080377	0.6973599	0.4990319
4757	-1.2448289	-0.0817113	0.5135511	-0.7589986	0.4307274	-0.8071260	A206	C306	-0.7716661	0.5467115	0.2755179	-0.2228202	-0.1702066	-0.7871317	0.4161209
4758	1.6023899	-0.8904536	2.2859986	2.7854017	0.4307274	-0.8071260	A419	C55	1.4810668	0.0181922	2.3175726	2.6287019	0.1225346	-0.2170130	0.3527581
4769	-0.2212849	0.6794579	0.4473277	-0.0501185	-0.6741149	-0.8071260	A246	C306	-0.7716661	0.5467115	0.2755179	-0.2228202	-0.1702066	-0.7871317	0.2585903
4787	-0.3078791	-0.8904536	0.4473277	-0.0501185	-0.6741149	-0.8071260	A198	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.3618326
4788	-0.3788864	0.6794579	0.0266149	-0.0501185	-0.6741149	-0.8071260	A224	C306	-0.7716661	0.5467115	0.2755179	-0.2228202	-0.1702066	-0.7871317	0.2451722
4790	-0.4654806	0.6794579	0.0266149	-0.0501185	0.4307274	-0.8071260	A276	C306	-0.7716661	0.5467115	0.2755179	-0.2228202	-0.1702066	-0.7871317	0.2469108
4793	0.1250921	0.6794579	2.2859986	-0.0501185	-0.6741149	-0.8071260	A319	C130	0.2826529	-0.0067137	1.6381330	0.9923522	0.2097590	-0.6177263	0.6012237
4796	1.4326652	0.6794579	2.2859986	2.7854017	0.4307274	-0.8071260	A421	C55	1.4810668	0.0181922	2.3175726	2.6287019	0.1225346	-0.2170130	0.2993745
4800	-0.7252634	0.6794579	0.5135511	-0.0501185	0.4307274	-0.8071260	A272	C306	-0.7716661	0.5467115	0.2755179	-0.2228202	-0.1702066	-0.7871317	0.2018021
4801	0.1562660	0.6794579	1.2342166	-0.0501185	0.4307274	-0.8071260	A303	C130	0.2826529	-0.0067137	1.6381330	0.9923522	0.2097590	-0.6177263	0.4448856
4805	-0.6300097	-0.8904536	0.4473277	-0.0501185	-0.6741149	-0.8071260	A186	C306	-0.7716661	0.5467115	0.2755179	-0.2228202	-0.1702066	-0.7871317	0.4078726
4810	-0.7252634	0.6794579	-0.7836469	-0.0501185	-0.6741149	-0.8071260	A150	C306	-0.7716661	0.5467115	0.2755179	-0.2228202	-0.1702066	-0.7871317	0.3224864
4813	-1.5912058	-0.8904536	-0.7914378	-0.7589986	-0.6741149	-0.8071260	A41	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.1440603
4817	0.6498532	-0.8904536	0.4473277	-0.0501185	-0.6741149	-0.8071260	A217	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.4308031
4825	-0.5676619	-0.8904536	0.4473277	-0.0501185	0.4307274	-0.8071260	A227	C306	-0.7716661	0.5467115	0.2755179	-0.2228202	-0.1702066	-0.7871317	0.4344349
4832	-0.1260312	0.6794579	0.0266149	-0.0501185	0.4307274	-0.8071260	A276	C306	-0.7716661	0.5467115	0.2755179	-0.2228202	-0.1702066	-0.7871317	0.3034857
4841	-0.0411688	-0.8904536	0.4473277	-0.0501185	-0.6741149	-0.8071260	A198	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.3173809
4842	0.2982806	-0.8904536	1.1952617	1.3676416	0.4307274	-0.8071260	A358	C130	0.2826529	-0.0067137	1.6381330	0.9923522	0.2097590	-0.6177263	0.3546494
4843	-1.5046116	-0.8904536	-0.7914378	-0.7589986	0.4307274	-0.8071260	A86	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.2635482
4845	0.4957155	-0.8904536	1.1952617	1.3676416	0.4307274	-0.8071260	A361	C130	0.2826529	-0.0067137	1.6381330	0.9923522	0.2097590	-0.6177263	0.3875552
4846	-0.9919737	0.6794579	-0.2850242	-0.0501185	-0.6741149	-0.8071260	A224	C306	-0.7716661	0.5467115	0.2755179	-0.2228202	-0.1702066	-0.7871317	0.2683667
4848	0.5476720	0.6794579	1.2342166	-0.0501185	2.6404120	-0.8071260	A387	C142	0.1328959	0.6627507	0.4814828	-0.0248014	2.6404120	-0.9712527	0.2289435
4849	1.5971943	0.6794579	2.2859986	2.7854017	0.4307274	-0.8071260	A421	C55	1.4810668	0.0181922	2.3175726	2.6287019	0.1225346	-0.2170130	0.3106621
4853	-0.8031982	0.6794579	-0.7758559	-0.7589986	-0.6741149	-0.8071260	A150	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.3656271
4858	0.1493385	-0.8904536	1.1952617	1.3676416	0.4307274	-0.4172552	A351	C130	0.2826529	-0.0067137	1.6381330	0.9923522	0.2097590	-0.6177263	0.3761091
4859	0.3848748	-0.8904536	1.1952617	1.3676416	0.4307274	-0.4172552	A351	C130	0.2826529	-0.0067137	1.6381330	0.9923522	0.2097590	-0.6177263	0.3709270
4862	1.4292014	0.6794579	2.2859986	2.7854017	0.4307274	-0.4172552	A421	C55	1.4810668	0.0181922	2.3175726	2.6287019	0.1225346	-0.2170130	0.2349733
4864	-1.1651622	-0.8904536	-0.7758559	-0.7589986	-0.6741149	-0.4172552	A66	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.1038304
4865	-0.6542561	-0.8904536	0.4473277	-0.0501185	0.4307274	-0.4172552	A227	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.4275351
4878	-0.9504084	0.6794579	0.0460923	-0.0501185	-0.6741149	-0.4172552	A224	C306	-0.7716661	0.5467115	0.2755179	-0.2228202	-0.1702066	-0.7871317	0.2645668
4886	0.2012950	0.6794579	1.2342166	-0.0501185	2.6404120	-0.4172552	A387	C142	0.1328959	0.6627507	0.4814828	-0.0248014	2.6404120	-0.9712527	0.2361925
4887	0.5632590	0.6794579	1.1952617	1.3676416	0.4307274	-0.4172552	A376	C130	0.2826529	-0.0067137	1.6381330	0.9923522	0.2097590	-0.6177263	0.3677297
4897	-0.2143573	-0.8904536	0.4473277	-0.0501185	-0.6741149	-0.4172552	A198	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.2812672
4907	-1.1738216	-0.8904536	-0.7758559	-0.7589986	-0.6741149	-0.4172552	A66	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.1023871
4916	-1.0006331	-0.8904536	-0.7758559	-0.7589986	-0.6741149	-0.4172552	A93	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.1312519
4919	-0.5590024	0.6794579	0.4473277	-0.0501185	-0.6741149	-0.4172552	A246	C306	-0.7716661	0.5467115	0.2755179	-0.2228202	-0.1702066	-0.7871317	0.2606177
4928	-0.5191691	0.6794579	0.4940736	-0.0501185	-0.6741149	-0.4172552	A246	C306	-0.7716661	0.5467115	0.2755179	-0.2228202	-0.1702066	-0.7871317	0.2750476
4938	-0.2749733	0.6794579	2.2859986	-0.0501185	0.4307274	-0.4172552	A339	C130	0.2826529	-0.0067137	1.6381330	0.9923522	0.2097590	-0.6177263	0.5592623
4947	-0.6230822	-0.0817113	0.4940736	-0.0501185	0.4307274	-0.4172552	A242	C306	-0.7716661	0.5467115	0.2755179	-0.2228202	-0.1702066	-0.7871317	0.3565124
4958	-1.0006331	-0.0817113	-0.7758559	-0.7589986	-0.6741149	-0.4172552	A116	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.2333178
4959	0.3034763	-0.8904536	1.1952617	1.3676416	0.4307274	-0.4172552	A351	C130	0.2826529	-0.0067137	1.6381330	0.9923522	0.2097590	-0.6177263	0.3573606
4964	0.0540848	0.6794579	-0.5577085	-0.0501185	-0.6741149	-0.4172552	A229	C326	0.4078813	0.4460352	-0.0758046	-0.2045827	-0.6741149	0.6597676	0.3834350
4974	1.1694187	-0.8904536	2.2859986	2.7854017	0.4307274	-0.4172552	A416	C55	1.4810668	0.0181922	2.3175726	2.6287019	0.1225346	-0.2170130	0.3195005
4976	-0.3615676	0.6794579	-0.5577085	-0.7589986	-0.6741149	-0.4172552	A146	C434	-0.4996726	0.3958051	-0.8430922	-0.8445203	-0.5645193	0.6623233	0.3303063
4989	-0.5364879	-0.0817113	0.4940736	-0.0501185	0.4307274	-0.4172552	A242	C306	-0.7716661	0.5467115	0.2755179	-0.2228202	-0.1702066	-0.7871317	0.3709448
4999	-0.0861979	0.6794579	2.2859986	-0.0501185	-0.6741149	-0.4172552	A319	C130	0.2826529	-0.0067137	1.6381330	0.9923522	0.2097590	-0.6177263	0.6382840
5005	-1.3331550	-0.8904536	-0.7836469	-0.7589986	-0.6741149	-0.4172552	A66	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.1272113
5007	0.3225270	-0.0817113	1.1952617	1.3676416	0.4307274	-0.4172552	A364	C130	0.2826529	-0.0067137	1.6381330	0.9923522	0.2097590	-0.6177263	0.2257453
5017	-1.0629809	-0.8904536	-0.7758559	-0.7589986	-0.6741149	-0.4172552	A93	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.1208606
5021	0.8334330	2.2969425	1.2342166	1.3676416	0.4307274	-0.4172552	A403	C57	0.1798241	1.6748331	2.0467757	1.3131124	0.3882335	-1.9684654	0.6227518
5022	-0.4810676	-0.0817113	0.4473277	-0.0501185	0.4307274	-0.4172552	A242	C306	-0.7716661	0.5467115	0.2755179	-0.2228202	-0.1702066	-0.7871317	0.3723906
5029	-1.0733723	-0.8904536	0.0421969	-0.7589986	-0.6741149	-0.4172552	A111	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.2301816
5033	-1.4180174	-0.8904536	0.0421969	-0.7589986	-0.6741149	-0.4172552	A111	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.2511094
5044	-0.1883791	0.6794579	0.0460923	-0.0501185	2.6404120	-0.4172552	A344	C142	0.1328959	0.6627507	0.4814828	-0.0248014	2.6404120	-0.9712527	0.2254479
5048	-1.0872273	-0.8904536	-0.7758559	-0.7589986	-0.6741149	-0.5382496	A66	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.0966538
5057	-0.5676619	-0.8904536	0.4473277	-0.0501185	-0.6741149	-0.5382496	A198	C384	-0.0359246	-0.9572228	0.0505756	-0.1222502	-0.6547317	0.5368788	0.3603170
5060	0.3554328	-0.0817113	1.1952617	1.3676416	0.4307274	-0.5382496	A364	C130	0.2826529	-0.0067137	1.6381330	0.9923522	0.2097590	-0.6177263	0.2110639
5064	0.1337515	-0.0817113	1.1952617	1.3676416	0.4307274	-0.5382496	A364	C130	0.2826529	-0.0067137	1.6381330	0.9923522	0.2097590	-0.6177263	0.2237508
5084	0.0627443	-0.8904536	1.1952617	1.3676416	0.4307274	-0.5382496	A351	C130	0.2826529	-0.0067137	1.6381330	0.9923522	0.2097590	-0.6177263	0.3703757
5096	-0.0394370	-0.8904536	1.1952617	1.3676416	0.4307274	-0.5382496	A351	C130	0.2826529	-0.0067137	1.6381330	0.9923522	0.2097590	-0.6177263	0.3874059
5106	-0.4239154	0.6794579	0.4473277	-0.0501185	-0.6741149	-0.5382496	A246	C306	-0.7716661	0.5467115	0.2755179	-0.2228202	-0.1702066	-0.7871317	0.2629665
5110	-1.5219304	-0.8904536	0.0421969	-0.7589986	-0.6741149	-0.5382496	A111	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.2482625
5113	-0.5676619	-0.8904536	0.4473277	-0.0501185	0.4307274	-0.5382496	A227	C414	-0.4728276	-0.8354472	-0.4305269	-0.4820923	0.4307274	0.6016920	0.4332684
5116	-1.0006331	0.6794579	-0.7758559	-0.7589986	-0.6741149	-0.5382496	A129	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.3400136
5129	-1.0214157	-0.0817113	0.0577788	-0.7589986	2.6404120	-0.5382496	A295	C142	0.1328959	0.6627507	0.4814828	-0.0248014	2.6404120	-0.9712527	0.5816130
5130	-1.0629809	0.6794579	-0.7758559	-0.7589986	-0.6741149	-0.5382496	A129	C478	-1.1829114	-0.7922801	-0.6999883	-0.7557764	-0.5234546	-0.6945646	0.3296222


hist(sorted_df$diff, breaks = 30, col = "blue", main = "Mean Absolute Difference", xlab = "Difference")

Figure 22: Mean Absolute Difference

muHVT: Predicting Cells with Layers using predictLayerHVT

Zubin Dowlaty, Srinivasan Sudarsanam, Somya Shambhawi

2023-06-29

1 Abstract

2 Example: muHVT with the Personal Computer dataset

3 Map A : Base Compressed Map

3.0.1 Iteration 1:

3.0.2 Iteration 2:

4 Map B : Compressed Novelty Map

4.1 Voronoi Tessellation with highlighted novelty cell

5 Map C : Compressed Map without Novelty

5.0.1 Iteration 1:

5.0.2 Iteration 2:

6 Prediction on Test Data

7 Executive Summary

8 References